maximuspowers/sig-autoencoder-fourier-5-supervised-mse
Updated
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29
Datasets:
example_id
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values | classification_text
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{"target_pattern": "palindrome", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2679, "learning_rate": 0.03008896643339405, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[27.498279, 35.283974, 35.418146, 38.875284, 172.342492], [19.224352, 19.405365, 21.672050, 23.269767, 40.157134], [23.507439, 29.406939, 32.954935, 34.787851, 133.596484], [38.741660, 38.815594, 47.029422, 49.955943, 335.818211], [23.055479, 23.188603, 23.241083, 23.481316, 24.315504], [17.102658, 17.657645, 17.694534, 17.816426, 29.607186], [19.507850, 21.795706, 22.664648, 24.276665, 137.376640]]
### 2
fourier: [[40.287682, 41.187411, 41.202411, 46.129979, 199.174496], [34.743216, 35.395008, 42.182779, 45.003143, 272.147350], [8.835680, 9.114747, 10.413997, 10.416229, 21.896036], [25.117635, 25.391281, 30.764091, 31.727574, 144.277895], [10.277922, 10.870554, 11.667284, 12.876762, 45.343093], [20.853944, 20.968147, 24.243720, 24.530710, 27.764364], [18.643271, 20.379379, 22.062686, 24.404145, 29.398139]]
### 4
fourier: [[13.818651, 15.791820, 15.929746, 16.942509, 19.448550], [13.543238, 14.440757, 14.915352, 16.161930, 39.533774], [57.788404, 58.170941, 62.081612, 68.760095, 289.021218], [29.174940, 30.169972, 31.464540, 35.204567, 190.042381], [48.523515, 49.033660, 52.366679, 56.003215, 199.656970], [35.557181, 36.210705, 36.980064, 42.678048, 169.198721], [15.021498, 15.161513, 17.223216, 21.845290, 109.438674]]
### 6
fourier: [[69.241334, 70.470012, 73.577161, 82.795648, 303.105409], [19.950616, 20.691390, 21.499032, 21.809799, 24.770378], [20.876270, 21.013904, 22.013972, 25.485761, 95.102164], [55.619008, 58.377489, 59.644260, 67.012870, 264.721055], [76.062463, 78.341500, 80.927729, 91.395173, 346.288437], [13.279422, 13.550805, 13.836597, 18.467447, 87.010923], [4.111265, 4.383868, 4.624238, 5.175402, 49.746099]]
### 8
fourier: [[37.600324, 39.451662, 39.493116, 45.340139, 182.098833], [30.262654, 31.006354, 31.211663, 36.766982, 184.850299], [149.288658, 154.604319, 156.771347, 178.455489, 636.848124], [75.869872, 76.934273, 78.098131, 90.692303, 395.220894], [59.756587, 60.740985, 62.329008, 73.028623, 312.679037], [12.588559, 13.100851, 13.315904, 16.156901, 116.595061], [16.609040, 17.649012, 17.744941, 18.125453, 51.484421]]
### 10
fourier: [[39.958965, 40.594823, 40.940176, 47.918136, 274.820479], [34.417995, 35.249284, 35.553769, 41.018977, 89.619845], [149.786760, 153.430714, 153.782049, 176.958861, 605.955853], [97.535934, 98.412603, 99.617574, 115.818923, 481.158469], [89.788328, 93.191932, 93.236046, 106.662181, 352.526668], [0.455789, 0.518563, 0.576235, 0.602953, 44.394372], [63.469423, 63.837588, 64.457559, 75.051447, 342.079193]]
### 12
fourier: [[110.324816, 110.880873, 112.380538, 128.201357, 450.767857]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
palindrome
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
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"network.12.bias": [
0.290096
]
}
## Activation Signature
### 0
fourier: [[27.498279, 35.283974, 35.418146, 38.875284, 172.342492], [19.224352, 19.405365, 21.672050, 23.269767, 40.157134], [23.507439, 29.406939, 32.954935, 34.787851, 133.596484], [38.741660, 38.815594, 47.029422, 49.955943, 335.818211], [23.055479, 23.188603, 23.241083, 23.481316, 24.315504], [17.102658, 17.657645, 17.694534, 17.816426, 29.607186], [19.507850, 21.795706, 22.664648, 24.276665, 137.376640]]
### 2
fourier: [[40.287682, 41.187411, 41.202411, 46.129979, 199.174496], [34.743216, 35.395008, 42.182779, 45.003143, 272.147350], [8.835680, 9.114747, 10.413997, 10.416229, 21.896036], [25.117635, 25.391281, 30.764091, 31.727574, 144.277895], [10.277922, 10.870554, 11.667284, 12.876762, 45.343093], [20.853944, 20.968147, 24.243720, 24.530710, 27.764364], [18.643271, 20.379379, 22.062686, 24.404145, 29.398139]]
### 4
fourier: [[13.818651, 15.791820, 15.929746, 16.942509, 19.448550], [13.543238, 14.440757, 14.915352, 16.161930, 39.533774], [57.788404, 58.170941, 62.081612, 68.760095, 289.021218], [29.174940, 30.169972, 31.464540, 35.204567, 190.042381], [48.523515, 49.033660, 52.366679, 56.003215, 199.656970], [35.557181, 36.210705, 36.980064, 42.678048, 169.198721], [15.021498, 15.161513, 17.223216, 21.845290, 109.438674]]
### 6
fourier: [[69.241334, 70.470012, 73.577161, 82.795648, 303.105409], [19.950616, 20.691390, 21.499032, 21.809799, 24.770378], [20.876270, 21.013904, 22.013972, 25.485761, 95.102164], [55.619008, 58.377489, 59.644260, 67.012870, 264.721055], [76.062463, 78.341500, 80.927729, 91.395173, 346.288437], [13.279422, 13.550805, 13.836597, 18.467447, 87.010923], [4.111265, 4.383868, 4.624238, 5.175402, 49.746099]]
### 8
fourier: [[37.600324, 39.451662, 39.493116, 45.340139, 182.098833], [30.262654, 31.006354, 31.211663, 36.766982, 184.850299], [149.288658, 154.604319, 156.771347, 178.455489, 636.848124], [75.869872, 76.934273, 78.098131, 90.692303, 395.220894], [59.756587, 60.740985, 62.329008, 73.028623, 312.679037], [12.588559, 13.100851, 13.315904, 16.156901, 116.595061], [16.609040, 17.649012, 17.744941, 18.125453, 51.484421]]
### 10
fourier: [[39.958965, 40.594823, 40.940176, 47.918136, 274.820479], [34.417995, 35.249284, 35.553769, 41.018977, 89.619845], [149.786760, 153.430714, 153.782049, 176.958861, 605.955853], [97.535934, 98.412603, 99.617574, 115.818923, 481.158469], [89.788328, 93.191932, 93.236046, 106.662181, 352.526668], [0.455789, 0.518563, 0.576235, 0.602953, 44.394372], [63.469423, 63.837588, 64.457559, 75.051447, 342.079193]]
### 12
fourier: [[110.324816, 110.880873, 112.380538, 128.201357, 450.767857]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome
|
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"activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}}
|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.532527, -0.008588, -0.120653, 0.372237, 0.630824], [0.14185, -0.218006, 0.404364, -0.348163, -0.270393], [0.411621, -0.403859, 0.129677, 0.29542, 0.549472], [-0.477765, -0.581331, -0.580646, -0.372518, -0.0425], [0.568815, 0.303227, -0.290788, -0.237894, 0.132969], [-0.287295, -0.242807, 0.114088, 0.276515, 0.38526], [0.048635, 0.237548, 0.463732, 0.283785, -0.31697]], "network.0.bias": [-0.056362, 0.009968, 0.126013, -0.01328, -0.218089, -0.177503, -0.153297], "network.2.weight": [[0.54605, -0.605648, 0.415587, -0.071809, 0.802062, 0.361553, -0.013516], [0.459568, 0.123855, 0.50106, -0.056918, 0.398468, 0.38168, 0.336133], [-0.340068, 0.409269, 0.223289, 0.158441, 0.12572, 0.358864, -0.242352], [0.309684, -0.439515, 0.343162, -0.05854, 0.271911, 0.632239, -0.1712], [-0.165289, 0.372538, 0.049155, 0.033148, -0.04476, -0.339744, 0.248131], [-0.21859, 0.603153, -0.359626, -0.040327, -0.501264, -0.00834, 0.351237], [-0.24229, 0.683003, -0.36028, 0.096108, -0.383439, 0.090239, 0.473521]], "network.2.bias": [-0.012409, 0.303944, 0.528917, 0.298849, 0.493885, 0.333546, 0.109153], "network.4.weight": [[0.196684, -0.00975, -0.549642, 0.135776, -0.610701, 0.065852, -0.310297], [-0.280072, -0.009497, 0.284771, 0.004301, 0.334801, 0.080055, 0.176941], [0.609483, 0.469932, -0.082926, 0.498587, -0.217199, -0.577574, -0.27205], [-0.393396, -0.170547, 0.257613, -0.342738, 0.018192, 0.152356, -0.335474], [0.6118, 0.246693, -0.724543, 0.50539, -0.307392, -0.333637, -0.209407], [0.469034, 0.42527, 0.097683, -0.038448, 0.050686, -0.472416, -0.140677], [-0.427575, 0.407068, 0.433653, -0.132639, 0.335021, 0.229808, 0.409346]], "network.4.bias": [0.149754, -0.189912, 0.088025, -0.171607, -0.073294, -0.230834, 0.55388], "network.6.weight": [[0.564444, -0.346307, 0.35078, 0.053559, 0.625325, 0.40277, -0.097358], [0.253124, 0.294131, 0.00249, -0.269322, -0.403244, 0.036947, 0.520948], [0.106911, -0.147957, -0.076351, -0.022261, -0.381954, -0.043272, -0.146326], [-0.014191, 0.063236, 0.356207, -0.351014, 0.349141, 0.464576, -0.524159], [0.091871, -0.278023, 0.744186, 0.302964, 0.464779, 0.258039, -0.329893], [-0.042322, 0.454578, 0.196868, -0.224052, -0.275301, -0.087502, 0.547364], [0.074824, -0.265201, 0.036594, -0.366282, -0.283016, 0.239691, -0.220127]], "network.6.bias": [-0.183082, 0.083503, 0.369553, 0.640302, 0.142767, 0.443794, -0.17301], "network.8.weight": [[-0.083157, 0.09884, 0.165833, -0.545572, 0.013628, 0.276317, 0.146636], [-0.430505, -0.048998, 0.055867, -0.322464, 0.194589, -0.220214, -0.017316], [0.702704, -0.563258, -0.264913, 0.71324, 0.712041, -0.671852, 0.116001], [0.224173, -0.107357, 0.039087, 0.469021, 0.44961, 0.00826, -0.203162], [0.344686, 0.354309, -0.316974, 0.145957, 0.421145, 0.131489, 0.364787], [0.013018, 0.463173, 0.308275, 0.231108, -0.180889, 0.585717, 0.355775], [-0.265094, 0.09269, 0.553873, 0.297002, -0.113979, 0.534299, 0.093935]], "network.8.bias": [-0.444394, -0.098547, 0.517419, 0.409638, -0.163206, 0.458802, 0.463186], "network.10.weight": [[0.106226, 0.048338, -0.248866, -0.272043, 0.215367, -0.241619, -0.243133], [0.298885, -0.021523, 0.02979, 0.075903, 0.330443, -0.187037, -0.341579], [0.087335, -0.097383, 0.673488, 0.476008, 0.107076, -0.32336, -0.65681], [-0.030551, -0.281656, -0.307566, -0.48723, -0.2355, -0.028955, 0.126186], [-0.163864, 0.004001, 0.18216, 0.327838, 0.488474, -0.440919, -0.630847], [-0.009095, 0.122767, -0.071826, -0.042486, 0.199495, 0.034381, -0.197043], [-0.178378, 0.151365, -0.326399, -0.335136, 0.147996, -0.000696, -0.128294]], "network.10.bias": [-0.251011, -0.218141, 0.159567, -0.147819, 0.489229, -0.353785, -0.292247], "network.12.weight": [[0.311048, -0.340006, -0.456531, -0.217959, -0.377487, -0.170107, -0.179423]], "network.12.bias": [0.290096]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6940549612045288, "train_acc": 0.43, "val_loss": 0.693019688129425, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6852896213531494, "train_acc": 0.58, "val_loss": 0.6840201020240784, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6705003976821899, "train_acc": 0.58, "val_loss": 0.6553263664245605, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6402151882648468, "train_acc": 0.505, "val_loss": 0.5648573637008667, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5624691247940063, "train_acc": 0.505, "val_loss": 0.48612916469573975, "val_acc": 0.48}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.47758589684963226, "train_acc": 0.65, "val_loss": 0.4447896480560303, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.469311460852623, "train_acc": 0.86, "val_loss": 0.4444141387939453, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.45776936411857605, "train_acc": 0.845, "val_loss": 0.43684670329093933, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4496414363384247, "train_acc": 0.815, "val_loss": 0.43263840675354004, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.41465140879154205, "train_acc": 0.855, "val_loss": 0.4251439571380615, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.47981125116348267, "train_acc": 0.855, "val_loss": 0.4039366543292999, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4038058966398239, "train_acc": 0.865, "val_loss": 0.38841795921325684, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.41814300417900085, "train_acc": 0.84, "val_loss": 0.3807235360145569, "val_acc": 0.88}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.693019688129425, "final_val_loss": 0.6553263664245605, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5648573637008667, "final_val_loss": 0.3807235360145569, "initial_val_acc": 0.48, "final_val_acc": 0.88, "best_val_acc": 0.94, "best_epoch": 9}, "improvement": 0.45999999999999996, "first_improvement_epoch": 2}}
|
1
|
{"target_pattern": "increasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.9, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7902, "learning_rate": 0.019119242316001303, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
0.212991,
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],
[
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-0.5352,
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],
[
0.457835,
0.19342,
0.07606,
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-0.153392
],
[
0.444877,
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0.369788,
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],
[
-0.275086,
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]
}
## Activation Signature
### 0
fourier: [[19.894860, 20.279078, 23.362255, 26.006243, 132.601268], [25.194370, 25.421897, 30.793058, 33.780405, 219.284541], [18.902309, 19.436765, 19.640993, 24.180657, 73.169833], [20.228130, 20.567323, 22.677624, 26.783678, 28.567112], [12.660138, 13.551450, 14.287381, 16.116807, 16.342166], [25.713531, 27.713904, 30.480989, 33.520348, 230.562905]]
### 2
fourier: [[8.836132, 9.379965, 9.566921, 9.582383, 85.075471], [9.581619, 10.255476, 10.686693, 11.736298, 80.364824], [8.975155, 9.700928, 10.893072, 11.767955, 13.188959], [6.855034, 7.033819, 7.269163, 8.808408, 14.985385], [8.891686, 9.464777, 9.495745, 9.567777, 88.922799], [9.811547, 13.689532, 15.671055, 16.433742, 81.708344]]
### 4
fourier: [[3.500327, 3.949093, 4.843928, 5.319395, 57.935501], [2.176085, 2.851323, 3.381766, 3.621666, 22.706448], [1.517241, 1.551647, 1.610664, 1.949002, 8.534282], [2.742621, 2.882993, 4.030734, 4.119908, 44.078834], [1.387385, 1.918392, 1.940004, 2.466097, 24.928429], [3.150953, 3.597430, 4.639009, 4.718723, 59.112374]]
### 6
fourier: [[4.026067, 4.477917, 5.646690, 6.043120, 85.163376], [2.305922, 2.611530, 3.135503, 3.476818, 30.543240], [1.305414, 1.398985, 1.691438, 1.930265, 20.969831], [3.446001, 3.630288, 4.691890, 5.028267, 79.055392], [0.319923, 0.327014, 0.336301, 0.375913, 5.487691], [3.061045, 3.391452, 4.364078, 4.635578, 69.464790]]
### 8
fourier: [[4.523699, 4.787034, 6.097042, 6.626563, 62.730791]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
increasing_pairs
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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]
],
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],
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"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[19.894860, 20.279078, 23.362255, 26.006243, 132.601268], [25.194370, 25.421897, 30.793058, 33.780405, 219.284541], [18.902309, 19.436765, 19.640993, 24.180657, 73.169833], [20.228130, 20.567323, 22.677624, 26.783678, 28.567112], [12.660138, 13.551450, 14.287381, 16.116807, 16.342166], [25.713531, 27.713904, 30.480989, 33.520348, 230.562905]]
### 2
fourier: [[8.836132, 9.379965, 9.566921, 9.582383, 85.075471], [9.581619, 10.255476, 10.686693, 11.736298, 80.364824], [8.975155, 9.700928, 10.893072, 11.767955, 13.188959], [6.855034, 7.033819, 7.269163, 8.808408, 14.985385], [8.891686, 9.464777, 9.495745, 9.567777, 88.922799], [9.811547, 13.689532, 15.671055, 16.433742, 81.708344]]
### 4
fourier: [[3.500327, 3.949093, 4.843928, 5.319395, 57.935501], [2.176085, 2.851323, 3.381766, 3.621666, 22.706448], [1.517241, 1.551647, 1.610664, 1.949002, 8.534282], [2.742621, 2.882993, 4.030734, 4.119908, 44.078834], [1.387385, 1.918392, 1.940004, 2.466097, 24.928429], [3.150953, 3.597430, 4.639009, 4.718723, 59.112374]]
### 6
fourier: [[4.026067, 4.477917, 5.646690, 6.043120, 85.163376], [2.305922, 2.611530, 3.135503, 3.476818, 30.543240], [1.305414, 1.398985, 1.691438, 1.930265, 20.969831], [3.446001, 3.630288, 4.691890, 5.028267, 79.055392], [0.319923, 0.327014, 0.336301, 0.375913, 5.487691], [3.061045, 3.391452, 4.364078, 4.635578, 69.464790]]
### 8
fourier: [[4.523699, 4.787034, 6.097042, 6.626563, 62.730791]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs
|
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|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.212991, -0.313221, 0.137815, -0.501964, -0.212779], [-0.219304, 0.03722, -0.521926, -0.5352, -0.17338], [0.457835, 0.19342, 0.07606, -0.181607, -0.153392], [0.444877, -0.276857, 0.369788, -0.243087, -0.151599], [-0.275086, -0.026804, 0.197148, 0.18607, -0.275863], [-0.139794, -0.0372, 0.206377, 0.43998, 0.677297]], "network.0.bias": [-0.116664, 0.22038, 0.310543, -0.190316, -0.203136, 0.593618], "network.2.weight": [[0.112299, 0.321055, -0.150767, 0.32421, 0.02298, -0.296143], [-0.307225, -0.153923, 0.023366, 0.106638, 0.135045, -0.338098], [0.034542, 0.163823, -0.276538, -0.316838, -0.419963, 0.193176], [-0.032634, -0.26626, -0.379844, 0.049524, -0.358898, 0.117517], [-0.137437, 0.276582, -0.074652, 0.261323, -0.014636, -0.297506], [0.110437, 0.027622, -0.142732, -0.189923, 0.343513, -0.394283]], "network.2.bias": [-0.207184, -0.13731, -0.112728, -0.121442, -0.281024, 0.220944], "network.4.weight": [[-0.539675, -0.269463, -0.560726, -0.034709, -0.405682, -0.457673], [0.107138, 0.034732, 0.19559, 0.405181, 0.195007, 0.567337], [-0.585728, -0.426504, -0.197462, 0.099564, -0.291907, -0.037711], [-0.412785, 0.069786, -0.378635, -0.236946, -0.193701, -0.189861], [-0.015004, 0.015074, 0.3505, -0.16422, 0.140709, 0.493939], [-0.367554, -0.203832, -0.198627, -0.599725, -0.542305, -0.420023]], "network.4.bias": [0.500061, -0.16749, -0.053877, 0.441248, -0.243658, 0.488397], "network.6.weight": [[0.33226, -0.496246, 0.297618, 0.235706, -0.485617, 0.641905], [-0.392533, 0.394066, -0.273973, 0.234261, 0.114105, -0.395679], [-0.365257, 0.18369, -0.259591, 0.011459, 0.0476, 0.044444], [0.617895, 0.113723, -0.14778, 0.185417, 0.207164, 0.612043], [0.121814, 0.395788, 0.027589, 0.240188, 0.343463, -0.014293], [0.323817, -0.343763, 0.004168, 0.504119, -0.608687, 0.189283]], "network.6.bias": [0.265196, 0.034389, -0.043228, 0.240906, -0.127366, 0.246031], "network.8.weight": [[-0.480462, 0.170579, 0.313318, -0.206584, -0.059553, -0.582244]], "network.8.bias": [0.239538]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7226835191249847, "train_acc": 0.425, "val_loss": 0.6928030252456665, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7008070349693298, "train_acc": 0.425, "val_loss": 0.6858577728271484, "val_acc": 0.88}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6851215362548828, "train_acc": 0.685, "val_loss": 0.6800218820571899, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6649401485919952, "train_acc": 0.575, "val_loss": 0.6705746650695801, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6510347425937653, "train_acc": 0.575, "val_loss": 0.6464852690696716, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6424163281917572, "train_acc": 0.525, "val_loss": 0.5864282250404358, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5881559252738953, "train_acc": 0.775, "val_loss": 0.518154501914978, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5365661680698395, "train_acc": 0.835, "val_loss": 0.4514089524745941, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4712718725204468, "train_acc": 0.835, "val_loss": 0.4069666564464569, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.41988661885261536, "train_acc": 0.86, "val_loss": 0.42357373237609863, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.3789648115634918, "train_acc": 0.85, "val_loss": 0.34573912620544434, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.33206671476364136, "train_acc": 0.85, "val_loss": 0.32399260997772217, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.35192015767097473, "train_acc": 0.845, "val_loss": 0.33109310269355774, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.3312777578830719, "train_acc": 0.855, "val_loss": 0.41086456179618835, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.36669476330280304, "train_acc": 0.865, "val_loss": 0.35528868436813354, "val_acc": 0.84}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6928030252456665, "final_val_loss": 0.6464852690696716, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5864282250404358, "final_val_loss": 0.35528868436813354, "initial_val_acc": 0.82, "final_val_acc": 0.84, "best_val_acc": 0.9, "best_epoch": 6}, "improvement": 0.4, "first_improvement_epoch": 4}}
|
2
|
{"target_pattern": "alternating", "degraded_accuracy": 0.52, "improved_accuracy": 0.84, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9451, "learning_rate": 0.07352170370310572, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[25.780001, 26.445519, 28.884864, 29.932559, 192.143096], [37.522940, 37.915636, 39.407108, 43.661955, 224.361521], [18.778436, 19.518605, 19.568951, 22.488656, 42.539715], [42.137199, 42.381991, 45.352526, 45.962375, 59.117496], [36.522290, 36.894504, 41.863646, 44.502690, 295.146933], [16.676502, 18.248927, 19.151383, 20.374897, 63.162612], [40.297459, 40.469734, 43.160487, 43.926349, 181.663065]]
### 2
fourier: [[10.259479, 10.438037, 10.883195, 11.455415, 13.428234], [15.929331, 17.259886, 18.346879, 20.624065, 98.864212], [6.025844, 6.455239, 7.474633, 8.607352, 14.433498], [30.263034, 30.700511, 32.882544, 33.359945, 217.989688], [12.543425, 13.075895, 13.146896, 14.005252, 19.424313], [25.587830, 26.159804, 28.830035, 30.572485, 202.938253], [9.249044, 9.515774, 10.493911, 11.626124, 24.722521]]
### 4
fourier: [[20.336644, 21.051058, 21.318042, 26.288254, 90.926861], [34.059173, 36.047393, 37.911622, 42.993594, 251.746032], [37.456983, 39.513698, 41.730925, 47.415404, 284.401585], [6.525796, 6.725557, 6.815865, 7.980023, 8.212054], [4.952122, 5.161641, 5.590594, 5.756533, 9.448708], [4.354498, 4.567505, 4.710304, 4.730569, 27.435410], [25.873164, 26.507103, 28.140326, 32.004881, 219.349749]]
### 6
fourier: [[14.639904, 16.433552, 17.188075, 17.971064, 66.616682], [32.773068, 33.273904, 36.844793, 41.283455, 200.741356], [4.674952, 4.747130, 4.769293, 4.910590, 5.321032], [31.986847, 34.010166, 36.544534, 38.973614, 223.028071], [12.046083, 13.503472, 14.787375, 15.639625, 52.880983], [13.312694, 15.230016, 15.860968, 16.148334, 92.753896], [45.004996, 46.213253, 50.055610, 58.008546, 328.438607]]
### 8
fourier: [[24.374903, 25.264611, 27.081444, 31.380196, 172.434747], [35.012611, 35.389289, 38.321351, 43.306735, 245.016882], [25.863985, 27.185132, 29.027445, 32.638238, 149.442304], [76.771073, 78.545707, 84.690425, 96.327525, 498.647108], [23.563067, 23.955252, 25.973118, 29.403741, 123.978915], [18.797472, 19.335740, 20.938659, 23.712177, 86.644597], [25.278297, 25.521255, 27.363732, 32.461461, 133.882767]]
### 10
fourier: [[56.601429, 58.120563, 61.802160, 70.380281, 332.671559]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
alternating
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[25.780001, 26.445519, 28.884864, 29.932559, 192.143096], [37.522940, 37.915636, 39.407108, 43.661955, 224.361521], [18.778436, 19.518605, 19.568951, 22.488656, 42.539715], [42.137199, 42.381991, 45.352526, 45.962375, 59.117496], [36.522290, 36.894504, 41.863646, 44.502690, 295.146933], [16.676502, 18.248927, 19.151383, 20.374897, 63.162612], [40.297459, 40.469734, 43.160487, 43.926349, 181.663065]]
### 2
fourier: [[10.259479, 10.438037, 10.883195, 11.455415, 13.428234], [15.929331, 17.259886, 18.346879, 20.624065, 98.864212], [6.025844, 6.455239, 7.474633, 8.607352, 14.433498], [30.263034, 30.700511, 32.882544, 33.359945, 217.989688], [12.543425, 13.075895, 13.146896, 14.005252, 19.424313], [25.587830, 26.159804, 28.830035, 30.572485, 202.938253], [9.249044, 9.515774, 10.493911, 11.626124, 24.722521]]
### 4
fourier: [[20.336644, 21.051058, 21.318042, 26.288254, 90.926861], [34.059173, 36.047393, 37.911622, 42.993594, 251.746032], [37.456983, 39.513698, 41.730925, 47.415404, 284.401585], [6.525796, 6.725557, 6.815865, 7.980023, 8.212054], [4.952122, 5.161641, 5.590594, 5.756533, 9.448708], [4.354498, 4.567505, 4.710304, 4.730569, 27.435410], [25.873164, 26.507103, 28.140326, 32.004881, 219.349749]]
### 6
fourier: [[14.639904, 16.433552, 17.188075, 17.971064, 66.616682], [32.773068, 33.273904, 36.844793, 41.283455, 200.741356], [4.674952, 4.747130, 4.769293, 4.910590, 5.321032], [31.986847, 34.010166, 36.544534, 38.973614, 223.028071], [12.046083, 13.503472, 14.787375, 15.639625, 52.880983], [13.312694, 15.230016, 15.860968, 16.148334, 92.753896], [45.004996, 46.213253, 50.055610, 58.008546, 328.438607]]
### 8
fourier: [[24.374903, 25.264611, 27.081444, 31.380196, 172.434747], [35.012611, 35.389289, 38.321351, 43.306735, 245.016882], [25.863985, 27.185132, 29.027445, 32.638238, 149.442304], [76.771073, 78.545707, 84.690425, 96.327525, 498.647108], [23.563067, 23.955252, 25.973118, 29.403741, 123.978915], [18.797472, 19.335740, 20.938659, 23.712177, 86.644597], [25.278297, 25.521255, 27.363732, 32.461461, 133.882767]]
### 10
fourier: [[56.601429, 58.120563, 61.802160, 70.380281, 332.671559]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating
|
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21.318042279533024, 26.28825380627806, 90.92686055600643]}, "1": {"fourier": [34.05917307115143, 36.04739327766241, 37.91162236810238, 42.99359402405017, 251.74603218585253]}, "2": {"fourier": [37.45698254382088, 39.513698055103596, 41.73092520987779, 47.41540398997817, 284.4015845954418]}, "3": {"fourier": [6.525795936792987, 6.725556776888612, 6.815865450805154, 7.980023429699015, 8.212054010171363]}, "4": {"fourier": [4.952122483994447, 5.161641122978325, 5.590594105288566, 5.756532775264074, 9.448707655072212]}, "5": {"fourier": [4.354497602062401, 4.567505025622141, 4.710303583801329, 4.730568856194777, 27.435409605503082]}, "6": {"fourier": [25.87316393494829, 26.50710335692444, 28.140326372263935, 32.00488138818019, 219.34974889457226]}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["fourier"]}}, "6": {"neuron_profiles": {"0": {"fourier": [14.639904482138842, 16.433551874638237, 17.188074667320226, 17.971064144656697, 66.61668212711811]}, "1": 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|
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|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6916628181934357, "train_acc": 0.545, "val_loss": 0.6948902606964111, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.656907469034195, "train_acc": 0.56, "val_loss": 0.6221851110458374, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5669578015804291, "train_acc": 0.57, "val_loss": 0.46326887607574463, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.36081814765930176, "train_acc": 0.935, "val_loss": 0.34990695118904114, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.33851301670074463, "train_acc": 0.865, "val_loss": 0.4313884973526001, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.24751634150743484, "train_acc": 0.92, "val_loss": 0.5466116070747375, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.22474919259548187, "train_acc": 0.91, "val_loss": 0.4689188301563263, "val_acc": 0.84}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.6948902606964111, "final_val_loss": 0.6221851110458374, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.46326887607574463, "final_val_loss": 0.4689188301563263, "initial_val_acc": 0.82, "final_val_acc": 0.84, "best_val_acc": 0.84, "best_epoch": 3}, "improvement": 0.31999999999999995, "first_improvement_epoch": 1}}
|
3
|
{"target_pattern": "increasing_pairs", "degraded_accuracy": 0.64, "improved_accuracy": 0.86, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9859, "learning_rate": 0.015384002471586396, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
0.74621,
0.228162,
-0.002776,
0.31816,
0.620733
],
[
0.357284,
-0.130418,
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0.454538,
0.176886
]
],
"network.2.bias": [
-0.0242,
0.008666,
-0.066052,
-0.083454,
-0.247497
],
"network.4.weight": [
[
0.028013,
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0.186128
],
[
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],
[
0.797567,
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[
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],
[
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]
],
"network.4.bias": [
-0.351487,
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-0.060313,
0.014951
],
"network.6.weight": [
[
0.390837,
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-0.381474,
-0.334873
],
[
-0.390806,
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0.086452,
0.105742
],
[
0.405974,
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0.717854
],
[
-0.213986,
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0.202157
],
[
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]
],
"network.6.bias": [
-0.026605,
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0.411154,
0.393598
],
"network.8.weight": [
[
-0.366589,
0.108788,
-0.632996,
0.34278,
0.114973
]
],
"network.8.bias": [
0.157994
]
}
## Activation Signature
### 0
fourier: [[20.330010, 22.752328, 26.059287, 26.542210, 90.256187], [24.296492, 24.565869, 24.587849, 26.151268, 176.539295], [27.471772, 28.256624, 29.222937, 32.669091, 171.742421], [27.741057, 29.686198, 30.527724, 30.658288, 35.193061], [27.287081, 28.137460, 28.880484, 32.703308, 34.265392]]
### 2
fourier: [[29.935099, 30.211064, 33.763059, 37.005793, 183.616194], [10.948788, 10.979886, 11.082227, 13.226420, 41.975265], [27.025734, 27.510969, 30.251748, 35.405263, 171.723387], [27.603145, 28.208573, 31.908557, 32.232268, 135.438536], [15.690366, 16.288634, 17.826516, 19.113160, 47.193890]]
### 4
fourier: [[2.205189, 2.244418, 2.316174, 2.430328, 37.394333], [4.435154, 4.661732, 4.678978, 6.073438, 55.038508], [48.495887, 52.028060, 57.282912, 61.002122, 287.535458], [33.531876, 35.822468, 38.931140, 42.818086, 204.118270], [43.114404, 45.350359, 49.783611, 53.223710, 248.346210]]
### 6
fourier: [[41.000092, 43.649006, 47.633182, 51.424633, 245.072689], [10.232274, 10.871688, 12.114530, 12.680249, 72.687809], [70.495497, 74.955306, 81.954677, 88.132039, 404.664256], [15.984437, 17.230330, 18.481317, 20.657930, 62.687127], [4.792653, 5.161780, 5.480291, 6.112224, 17.292335]]
### 8
fourier: [[45.283496, 47.788929, 52.488777, 56.663473, 237.192383]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
increasing_pairs
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.133872,
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],
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],
[
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0.229654,
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],
[
0.588696,
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0.131112,
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0.197309
],
[
0.022387,
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
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[
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[
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"network.4.bias": [
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],
"network.6.weight": [
[
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],
[
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[
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[
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[
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],
"network.6.bias": [
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],
"network.8.weight": [
[
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0.108788,
-0.632996,
0.34278,
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]
],
"network.8.bias": [
0.157994
]
}
## Activation Signature
### 0
fourier: [[20.330010, 22.752328, 26.059287, 26.542210, 90.256187], [24.296492, 24.565869, 24.587849, 26.151268, 176.539295], [27.471772, 28.256624, 29.222937, 32.669091, 171.742421], [27.741057, 29.686198, 30.527724, 30.658288, 35.193061], [27.287081, 28.137460, 28.880484, 32.703308, 34.265392]]
### 2
fourier: [[29.935099, 30.211064, 33.763059, 37.005793, 183.616194], [10.948788, 10.979886, 11.082227, 13.226420, 41.975265], [27.025734, 27.510969, 30.251748, 35.405263, 171.723387], [27.603145, 28.208573, 31.908557, 32.232268, 135.438536], [15.690366, 16.288634, 17.826516, 19.113160, 47.193890]]
### 4
fourier: [[2.205189, 2.244418, 2.316174, 2.430328, 37.394333], [4.435154, 4.661732, 4.678978, 6.073438, 55.038508], [48.495887, 52.028060, 57.282912, 61.002122, 287.535458], [33.531876, 35.822468, 38.931140, 42.818086, 204.118270], [43.114404, 45.350359, 49.783611, 53.223710, 248.346210]]
### 6
fourier: [[41.000092, 43.649006, 47.633182, 51.424633, 245.072689], [10.232274, 10.871688, 12.114530, 12.680249, 72.687809], [70.495497, 74.955306, 81.954677, 88.132039, 404.664256], [15.984437, 17.230330, 18.481317, 20.657930, 62.687127], [4.792653, 5.161780, 5.480291, 6.112224, 17.292335]]
### 8
fourier: [[45.283496, 47.788929, 52.488777, 56.663473, 237.192383]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs
|
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|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.490584, -0.00563, 0.319729, 0.133872, -0.346727], [-0.103028, -0.084305, -0.143168, -0.464692, -0.380329], [0.768259, 0.135435, 0.004555, 0.229654, -0.385615], [0.588696, -0.004258, 0.131112, -0.502869, 0.197309], [0.022387, 0.049253, 0.715397, -0.517478, -0.206524]], "network.0.bias": [-0.124728, 0.084928, 0.678998, 0.175504, -0.061403], "network.2.weight": [[0.45404, -0.185016, 0.609076, 0.279465, 0.164092], [-0.107602, 0.009283, 0.043065, 0.06165, 0.5785], [0.49012, -0.103306, 0.539643, 0.073985, 0.402948], [0.74621, 0.228162, -0.002776, 0.31816, 0.620733], [0.357284, -0.130418, -0.082328, 0.454538, 0.176886]], "network.2.bias": [-0.0242, 0.008666, -0.066052, -0.083454, -0.247497], "network.4.weight": [[0.028013, 0.312583, -0.064444, -0.171507, 0.186128], [0.180827, 0.054785, -0.261857, -0.272733, 0.337052], [0.797567, 0.563818, 0.137688, 0.655687, 0.112381], [0.502159, 0.403582, 0.619295, -0.212464, 0.408551], [0.564177, -0.105083, 0.538794, 0.161385, 0.599117]], "network.4.bias": [-0.351487, -0.300211, -0.023558, -0.060313, 0.014951], "network.6.weight": [[0.390837, -0.374882, -0.283566, -0.381474, -0.334873], [-0.390806, -0.397559, -0.360419, 0.086452, 0.105742], [0.405974, 0.299639, 0.543026, 0.393541, 0.717854], [-0.213986, -0.03172, -0.032995, -0.687058, 0.202157], [0.219681, 0.139951, -0.512758, 0.294143, 0.278773]], "network.6.bias": [-0.026605, -0.14395, -0.113505, 0.411154, 0.393598], "network.8.weight": [[-0.366589, 0.108788, -0.632996, 0.34278, 0.114973]], "network.8.bias": [0.157994]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6973071992397308, "train_acc": 0.455, "val_loss": 0.7012566328048706, "val_acc": 0.36}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6948840916156769, "train_acc": 0.465, "val_loss": 0.6941952705383301, "val_acc": 0.4}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6907375156879425, "train_acc": 0.545, "val_loss": 0.6863901019096375, "val_acc": 0.64}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6879516839981079, "train_acc": 0.545, "val_loss": 0.6768937706947327, "val_acc": 0.64}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6836244463920593, "train_acc": 0.545, "val_loss": 0.6647509932518005, "val_acc": 0.64}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6864051222801208, "train_acc": 0.465, "val_loss": 0.6539306640625, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.664957731962204, "train_acc": 0.465, "val_loss": 0.6319841146469116, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6367122530937195, "train_acc": 0.525, "val_loss": 0.5913990139961243, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5929924547672272, "train_acc": 0.8, "val_loss": 0.5391824841499329, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5497379004955292, "train_acc": 0.85, "val_loss": 0.48523783683776855, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.5030532777309418, "train_acc": 0.83, "val_loss": 0.44129738211631775, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.48471327126026154, "train_acc": 0.84, "val_loss": 0.4045620858669281, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.43414998054504395, "train_acc": 0.86, "val_loss": 0.37801170349121094, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.4018976092338562, "train_acc": 0.89, "val_loss": 0.3526187241077423, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.372944712638855, "train_acc": 0.9, "val_loss": 0.3303980231285095, "val_acc": 0.86}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7012566328048706, "final_val_loss": 0.6647509932518005, "initial_val_acc": 0.36, "final_val_acc": 0.64, "best_val_acc": 0.64}, "improved_stage": {"initial_val_loss": 0.6539306640625, "final_val_loss": 0.3303980231285095, "initial_val_acc": 0.64, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 12}, "improvement": 0.21999999999999997, "first_improvement_epoch": 4}}
|
4
|
{"target_pattern": "sorted_descending", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4854, "learning_rate": 0.09414589333639692, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.020692,
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0.075373,
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],
[
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0.110873,
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[
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[
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],
[
-0.341909,
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[
0.005497,
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## Activation Signature
### 0
fourier: [[19.333642, 19.518000, 22.458752, 25.777915, 182.424958], [28.600942, 29.070845, 30.291533, 31.600757, 123.991215], [20.645746, 22.821425, 22.991149, 23.246510, 59.616262], [30.048121, 32.566662, 34.039622, 38.145512, 175.806779], [21.611664, 22.245804, 26.091783, 26.334799, 26.457979], [24.306618, 25.628002, 29.807172, 30.142874, 235.612087], [23.423922, 23.814901, 28.615617, 29.418931, 47.565534], [25.313468, 26.133300, 26.717423, 26.800134, 81.356713]]
### 2
fourier: [[14.253677, 15.400921, 15.628642, 20.579092, 150.752914], [15.858093, 17.244323, 18.092314, 18.109106, 19.314918], [18.007437, 18.075103, 18.925236, 20.938304, 25.566078], [21.746439, 22.903604, 23.025498, 29.135445, 247.081152], [28.084637, 29.724193, 31.652763, 43.258036, 75.187383], [34.353883, 35.016718, 36.123987, 46.357339, 151.095363], [37.631773, 38.040771, 38.789020, 54.681335, 114.867529], [24.573029, 25.068696, 25.197923, 30.373347, 98.865981]]
### 4
fourier: [[58.409171, 58.918131, 63.990883, 74.430277, 304.326805], [60.122534, 60.343988, 66.312250, 77.069832, 342.816209], [14.411476, 14.659718, 16.122013, 18.130431, 50.806417], [33.188151, 33.563597, 37.804728, 45.726861, 178.224296], [19.448834, 21.097559, 22.985769, 25.656611, 170.469566], [9.824057, 9.911635, 10.097163, 10.344473, 47.041090], [0.768924, 1.104460, 1.217463, 1.243637, 32.407142], [11.490416, 11.825979, 12.598457, 14.064622, 90.109703]]
### 6
fourier: [[38.486858, 38.670214, 42.732516, 49.579206, 183.655095], [19.853696, 20.024719, 21.861016, 24.810803, 134.866193], [12.997586, 13.327442, 14.628649, 16.178508, 79.411926], [14.327744, 14.409157, 15.598471, 18.629121, 115.382514], [51.877222, 52.079355, 57.085184, 67.902986, 287.722601], [19.426444, 19.632676, 21.243930, 24.838000, 126.401144], [51.991449, 52.288633, 57.778907, 67.847617, 251.865241], [52.889471, 53.231174, 58.182335, 68.803191, 304.591213]]
### 8
fourier: [[24.585308, 24.608388, 26.441323, 31.291888, 108.861972]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
sorted_descending
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[19.333642, 19.518000, 22.458752, 25.777915, 182.424958], [28.600942, 29.070845, 30.291533, 31.600757, 123.991215], [20.645746, 22.821425, 22.991149, 23.246510, 59.616262], [30.048121, 32.566662, 34.039622, 38.145512, 175.806779], [21.611664, 22.245804, 26.091783, 26.334799, 26.457979], [24.306618, 25.628002, 29.807172, 30.142874, 235.612087], [23.423922, 23.814901, 28.615617, 29.418931, 47.565534], [25.313468, 26.133300, 26.717423, 26.800134, 81.356713]]
### 2
fourier: [[14.253677, 15.400921, 15.628642, 20.579092, 150.752914], [15.858093, 17.244323, 18.092314, 18.109106, 19.314918], [18.007437, 18.075103, 18.925236, 20.938304, 25.566078], [21.746439, 22.903604, 23.025498, 29.135445, 247.081152], [28.084637, 29.724193, 31.652763, 43.258036, 75.187383], [34.353883, 35.016718, 36.123987, 46.357339, 151.095363], [37.631773, 38.040771, 38.789020, 54.681335, 114.867529], [24.573029, 25.068696, 25.197923, 30.373347, 98.865981]]
### 4
fourier: [[58.409171, 58.918131, 63.990883, 74.430277, 304.326805], [60.122534, 60.343988, 66.312250, 77.069832, 342.816209], [14.411476, 14.659718, 16.122013, 18.130431, 50.806417], [33.188151, 33.563597, 37.804728, 45.726861, 178.224296], [19.448834, 21.097559, 22.985769, 25.656611, 170.469566], [9.824057, 9.911635, 10.097163, 10.344473, 47.041090], [0.768924, 1.104460, 1.217463, 1.243637, 32.407142], [11.490416, 11.825979, 12.598457, 14.064622, 90.109703]]
### 6
fourier: [[38.486858, 38.670214, 42.732516, 49.579206, 183.655095], [19.853696, 20.024719, 21.861016, 24.810803, 134.866193], [12.997586, 13.327442, 14.628649, 16.178508, 79.411926], [14.327744, 14.409157, 15.598471, 18.629121, 115.382514], [51.877222, 52.079355, 57.085184, 67.902986, 287.722601], [19.426444, 19.632676, 21.243930, 24.838000, 126.401144], [51.991449, 52.288633, 57.778907, 67.847617, 251.865241], [52.889471, 53.231174, 58.182335, 68.803191, 304.591213]]
### 8
fourier: [[24.585308, 24.608388, 26.441323, 31.291888, 108.861972]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending
|
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|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.020692, -0.651551, 0.075373, -0.049835, -0.175731], [-0.490529, -0.340971, 0.110873, 0.553264, 0.606139], [-0.087405, -0.406463, 0.12351, 0.652596, -0.381449], [0.893046, -0.031361, 0.078451, 0.366671, -0.172915], [-0.341909, -0.181946, -0.162101, 0.564754, -0.064637], [0.005497, -0.442614, -0.091421, -0.409622, -0.321745], [-0.375175, 0.045922, -0.290128, 0.327733, -0.295627], [-0.490387, 0.063055, -0.049087, 0.17886, 0.712208]], "network.0.bias": [-0.699266, 0.443823, 0.324839, 0.16229, -0.328329, -0.352013, 0.122544, 0.239916], "network.2.weight": [[-0.479875, -0.004748, -0.269473, -0.361379, -0.235998, 0.046999, -0.361028, -0.242454], [-0.229346, -0.235581, 0.429385, 0.338963, -0.026256, -0.260977, -0.416519, -0.242195], [-0.341816, 0.034091, 0.599171, -0.271976, 0.698023, 0.177662, -0.215815, 0.144467], [0.048361, -0.192044, -0.203077, -0.56429, -0.305309, 0.003926, -0.289593, -0.338048], [0.465371, 0.457431, 0.569819, -0.500858, 0.547041, -0.114418, -0.009211, 0.159923], [-0.260898, 0.482687, 0.7342, -0.269168, 0.667262, -0.33238, 0.030264, 0.42472], [-0.324823, 0.652147, 0.526026, -0.562716, 0.935478, -0.12036, 0.059044, 0.194735], [-0.057856, 0.447569, 0.456576, -0.119793, 0.655062, -0.351053, -0.187033, 0.117999]], "network.2.bias": [-0.205857, -0.316097, -0.476759, -0.509702, 0.089941, -0.084686, 0.118202, -0.224007], "network.4.weight": [[0.005203, 0.297972, 0.145057, 0.008915, 0.639092, 0.671256, 0.391214, 0.457129], [0.048379, 0.473792, 0.045427, 0.535599, 0.733297, 0.76602, 0.402803, 0.365211], [0.385767, -0.247329, 0.106896, 0.431539, 0.243605, -0.022971, -0.436741, -0.33044], [0.239516, 0.322398, -0.179253, 0.009443, 0.848964, 0.406451, 0.358902, -0.236295], [-0.153422, -0.481724, 0.091868, -0.226576, -0.233929, -0.152361, -0.350272, -0.065038], [0.328131, 0.205971, -0.411153, 0.293737, 0.128735, 0.211271, -0.315583, -0.161906], [-0.18699, -0.097596, -0.013128, 0.169829, -0.184505, 0.147711, -0.048135, 0.027359], [0.252833, 0.03447, -0.283017, -0.071841, -0.36452, -0.025828, -0.037222, 0.088584]], "network.4.bias": [-0.111567, 0.102418, 0.360941, -0.214437, -0.503371, -0.189103, -0.311589, -0.39375], "network.6.weight": [[0.248079, 0.355103, -0.275881, 0.07508, -0.233638, -0.088319, 0.001423, 0.126851], [-0.131862, -0.331597, 0.086474, 0.234137, 0.3095, -0.238337, -0.302186, -0.232704], [-0.2999, -0.053468, 0.308114, 0.23342, -0.35204, -0.337733, 0.283981, -0.339767], [0.115329, -0.293754, -0.257193, -0.106409, -0.254996, -0.044153, 0.042363, 0.280874], [-0.361535, -0.221839, -0.313945, -0.529774, -0.052776, -0.555494, -0.069123, 0.067854], [-0.180653, -0.156951, -0.107795, 0.013709, 0.282067, -0.025399, 0.111302, -0.226032], [0.38978, 0.264957, -0.22169, 0.397582, -0.098587, 0.056463, -0.010884, -0.131857], [-0.074418, -0.624164, -0.382713, -0.340753, -0.270624, -0.276418, 0.274616, -0.082277]], "network.6.bias": [-0.278431, -0.257928, -0.145847, -0.320486, -0.035375, -0.2139, -0.307531, -0.03992], "network.8.weight": [[-0.248132, -0.249554, 0.131497, -0.351041, 0.094175, -0.212405, -0.285732, 0.010686]], "network.8.bias": [0.116247]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6972275674343109, "train_acc": 0.565, "val_loss": 0.6631535291671753, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6324674189090729, "train_acc": 0.565, "val_loss": 0.5520926117897034, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6268877387046814, "train_acc": 0.485, "val_loss": 0.6345001459121704, "val_acc": 0.56}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6289696097373962, "train_acc": 0.65, "val_loss": 0.4009753465652466, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4610057771205902, "train_acc": 0.875, "val_loss": 0.4616139233112335, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.39319078624248505, "train_acc": 0.905, "val_loss": 0.31102287769317627, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3505774438381195, "train_acc": 0.895, "val_loss": 0.28951141238212585, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.326407253742218, "train_acc": 0.88, "val_loss": 0.2592458426952362, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.279848650097847, "train_acc": 0.89, "val_loss": 0.3373497724533081, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.3128812164068222, "train_acc": 0.91, "val_loss": 0.27206963300704956, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.28574925661087036, "train_acc": 0.905, "val_loss": 0.2719041109085083, "val_acc": 0.9}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6631535291671753, "final_val_loss": 0.5520926117897034, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.6345001459121704, "final_val_loss": 0.2719041109085083, "initial_val_acc": 0.56, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 3}, "improvement": 0.3799999999999999, "first_improvement_epoch": 1}}
|
5
|
{"target_pattern": "has_majority", "degraded_accuracy": 0.38, "improved_accuracy": 0.68, "improvement": 0.30000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8556, "learning_rate": 0.09363094593146719, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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0.0753
],
[
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[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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[
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]
],
"network.8.bias": [
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]
}
## Activation Signature
### 0
fourier: [[27.476031, 28.667703, 30.080435, 37.457144, 57.286178], [16.012570, 16.621874, 18.283121, 19.158511, 101.680914], [21.050371, 21.840614, 22.568467, 27.156694, 54.218007], [21.417931, 21.820629, 22.383376, 24.458430, 26.999214], [20.058744, 22.610332, 22.696731, 24.115968, 107.389378]]
### 2
fourier: [[10.225397, 10.486088, 10.628317, 13.326365, 85.252838], [12.960431, 14.658314, 16.247973, 18.135024, 40.335139], [3.407128, 3.416844, 3.866126, 4.016277, 56.538303], [16.108105, 17.019122, 17.126850, 17.205182, 51.550891], [5.750303, 6.185852, 6.600524, 8.209970, 24.042568]]
### 4
fourier: [[5.167193, 6.053736, 6.115134, 6.287086, 33.939417], [2.662140, 2.971680, 3.019938, 3.247300, 72.402764], [8.329681, 8.473186, 8.920279, 9.768523, 93.473086], [6.421775, 6.883780, 7.669991, 9.726426, 23.411209], [5.848433, 5.885763, 6.978538, 7.053212, 23.633471]]
### 6
fourier: [[2.304966, 2.338498, 2.749897, 3.156173, 6.805523], [1.198176, 1.265129, 1.460272, 1.549752, 47.926659], [1.695478, 1.733957, 2.113089, 2.276753, 50.900413], [2.271255, 2.345925, 2.692997, 3.072019, 18.691757], [0.751549, 0.798594, 0.804400, 0.997093, 45.171380]]
### 8
fourier: [[1.932892, 1.979020, 2.340613, 2.624736, 38.939777]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
has_majority
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
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],
[
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[
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[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
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}
## Activation Signature
### 0
fourier: [[27.476031, 28.667703, 30.080435, 37.457144, 57.286178], [16.012570, 16.621874, 18.283121, 19.158511, 101.680914], [21.050371, 21.840614, 22.568467, 27.156694, 54.218007], [21.417931, 21.820629, 22.383376, 24.458430, 26.999214], [20.058744, 22.610332, 22.696731, 24.115968, 107.389378]]
### 2
fourier: [[10.225397, 10.486088, 10.628317, 13.326365, 85.252838], [12.960431, 14.658314, 16.247973, 18.135024, 40.335139], [3.407128, 3.416844, 3.866126, 4.016277, 56.538303], [16.108105, 17.019122, 17.126850, 17.205182, 51.550891], [5.750303, 6.185852, 6.600524, 8.209970, 24.042568]]
### 4
fourier: [[5.167193, 6.053736, 6.115134, 6.287086, 33.939417], [2.662140, 2.971680, 3.019938, 3.247300, 72.402764], [8.329681, 8.473186, 8.920279, 9.768523, 93.473086], [6.421775, 6.883780, 7.669991, 9.726426, 23.411209], [5.848433, 5.885763, 6.978538, 7.053212, 23.633471]]
### 6
fourier: [[2.304966, 2.338498, 2.749897, 3.156173, 6.805523], [1.198176, 1.265129, 1.460272, 1.549752, 47.926659], [1.695478, 1.733957, 2.113089, 2.276753, 50.900413], [2.271255, 2.345925, 2.692997, 3.072019, 18.691757], [0.751549, 0.798594, 0.804400, 0.997093, 45.171380]]
### 8
fourier: [[1.932892, 1.979020, 2.340613, 2.624736, 38.939777]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority
|
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|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.806191, 0.058736, 0.106688, 0.155203, -0.106613], [-0.18633, 0.200702, 0.455795, 0.140616, 0.0753], [0.187287, -0.254269, -0.617336, 0.287278, 0.16774], [0.123714, -0.502213, 0.359428, 0.076761, -0.623068], [-0.047339, 0.545939, 0.130231, 0.150369, -0.180265]], "network.0.bias": [-0.164478, -0.350575, 0.094459, 0.342466, -0.114864], "network.2.weight": [[-0.016052, -0.546835, 0.170126, 0.30434, -0.108982], [0.075998, -0.642997, -0.12049, -0.533819, 0.539945], [-0.222866, -0.165909, 0.335092, 0.294867, 0.196344], [0.280217, 0.121205, -0.723858, -0.684204, 0.475178], [-0.002892, 0.079338, 0.213129, 0.4954, -0.155166]], "network.2.bias": [-0.327337, -0.210842, 0.487007, 0.147155, -0.343049], "network.4.weight": [[0.301031, -0.094571, 0.156193, -0.413762, -0.17439], [0.485175, 0.133885, -0.191866, -0.168314, 0.486071], [0.908536, -0.119773, -0.329191, -0.59348, 0.229267], [0.860155, -0.118355, -0.67354, 0.523856, 0.455411], [-0.556116, -0.318277, -0.236545, -0.417335, -0.279005]], "network.4.bias": [-0.181364, -0.529888, -0.414629, -0.131773, 0.016287], "network.6.weight": [[-0.052589, 0.446114, 0.022683, 0.640097, -0.177296], [-0.419822, 0.56316, -0.033848, -0.428661, 0.019023], [-0.11058, 0.088171, -0.528665, -0.507884, -0.198976], [0.117892, -0.708541, -0.285174, -0.634031, -0.085727], [-0.220327, -0.12755, -0.033687, 0.280538, 0.348598]], "network.6.bias": [0.007572, -0.501224, 0.465113, 0.035817, -0.518457], "network.8.weight": [[-0.533498, -0.392209, 0.606311, 0.33855, -0.178867]], "network.8.bias": [0.038218]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6722663342952728, "train_acc": 0.6, "val_loss": 0.7984893918037415, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6620895564556122, "train_acc": 0.6, "val_loss": 0.8409619331359863, "val_acc": 0.38}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6625472605228424, "train_acc": 0.6, "val_loss": 0.7251842021942139, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.7453276813030243, "train_acc": 0.53, "val_loss": 0.6542050242424011, "val_acc": 0.62}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.665235310792923, "train_acc": 0.6, "val_loss": 0.6298772692680359, "val_acc": 0.68}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.6834256947040558, "train_acc": 0.54, "val_loss": 0.6297533512115479, "val_acc": 0.68}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.6258291006088257, "train_acc": 0.66, "val_loss": 0.662627100944519, "val_acc": 0.62}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.6246632933616638, "train_acc": 0.67, "val_loss": 0.7042602300643921, "val_acc": 0.58}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.5746208131313324, "train_acc": 0.7, "val_loss": 0.5853145718574524, "val_acc": 0.64}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.5037030279636383, "train_acc": 0.735, "val_loss": 0.5997480750083923, "val_acc": 0.68}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.5731785297393799, "train_acc": 0.735, "val_loss": 0.5713573694229126, "val_acc": 0.64}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.47621485590934753, "train_acc": 0.745, "val_loss": 0.6736403703689575, "val_acc": 0.56}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.5069227069616318, "train_acc": 0.705, "val_loss": 0.6214319467544556, "val_acc": 0.58}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.7984893918037415, "final_val_loss": 0.7251842021942139, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.6542050242424011, "final_val_loss": 0.6214319467544556, "initial_val_acc": 0.62, "final_val_acc": 0.58, "best_val_acc": 0.68, "best_epoch": 4}, "improvement": 0.30000000000000004, "first_improvement_epoch": 2}}
|
6
|
{"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.98, "improvement": 0.48, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9319, "learning_rate": 0.04720846293947128, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}}
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
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0.175211,
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],
"network.8.bias": [
0.433319,
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0.078354,
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0.259427,
0.279504,
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"network.10.weight": [
[
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0.076149,
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],
"network.10.bias": [
0.159497
]
}
## Activation Signature
### 0
fourier: [[20.791790, 23.628495, 23.985589, 24.265644, 30.409205], [36.371457, 39.472281, 42.518940, 44.495319, 164.936075], [22.209946, 22.334364, 22.620061, 23.468327, 170.300977], [27.335724, 28.348592, 30.444751, 39.147652, 77.070102], [33.336845, 36.885108, 40.480283, 41.009265, 249.842542], [24.513595, 27.501147, 27.646671, 34.059340, 109.742055], [28.207286, 28.347215, 32.081336, 34.876825, 162.033303], [21.497039, 23.336308, 25.566767, 28.130060, 29.044346]]
### 2
fourier: [[20.238895, 22.024668, 23.562066, 26.300144, 67.774865], [25.014779, 28.284839, 28.787497, 32.573184, 51.301648], [22.491110, 23.599723, 23.934437, 28.155893, 97.028675], [21.626599, 22.237937, 22.508200, 23.125751, 67.270212], [19.068251, 20.791543, 22.433152, 24.822831, 132.947022], [53.161498, 53.599468, 53.610454, 53.778861, 170.564538], [12.311284, 12.357461, 15.780656, 19.874317, 121.610069], [19.479906, 20.028452, 20.474303, 22.290788, 74.459058]]
### 4
fourier: [[26.611392, 26.678879, 27.460002, 27.700512, 76.411671], [21.094542, 21.136092, 24.901375, 32.659857, 251.737920], [11.679655, 11.844030, 11.964151, 13.790272, 62.598181], [24.966886, 29.499541, 33.730882, 35.567228, 175.143204], [18.943261, 19.211392, 19.944621, 21.548124, 104.506999], [36.234606, 36.642665, 39.583224, 39.728688, 45.804259], [9.517819, 10.541905, 12.503196, 14.442512, 60.362703], [10.477869, 10.912812, 14.244717, 17.167496, 88.168987]]
### 6
fourier: [[8.120829, 8.159488, 8.828038, 10.055844, 97.410089], [19.221020, 20.139617, 21.005114, 29.626824, 247.383277], [35.514181, 37.228915, 46.542954, 57.118829, 418.902289], [44.001085, 46.330877, 49.390199, 53.371945, 57.683844], [39.672627, 40.961421, 56.013025, 61.665204, 331.173141], [31.908231, 32.927545, 43.146206, 47.594768, 217.675501], [27.767470, 29.253049, 39.371156, 42.067236, 194.336412], [7.170912, 7.316240, 7.658174, 7.874093, 33.958100]]
### 8
fourier: [[60.993995, 65.037381, 85.355646, 93.413550, 391.532422], [91.631559, 92.984069, 121.598374, 141.271594, 858.908078], [75.389068, 78.083643, 102.598761, 115.764796, 665.780063], [20.519617, 20.593853, 26.873411, 31.465753, 176.962122], [17.103719, 18.721072, 23.001545, 27.783385, 222.290445], [69.175255, 71.833665, 94.080517, 106.173510, 595.913794], [86.931850, 89.621114, 117.447582, 133.871269, 759.836808], [6.261078, 7.139272, 7.818134, 10.739841, 138.005144]]
### 10
fourier: [[187.157036, 197.562025, 249.781685, 290.722507, 1723.355606]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
|
decreasing_pairs
|
## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
fourier: [[20.791790, 23.628495, 23.985589, 24.265644, 30.409205], [36.371457, 39.472281, 42.518940, 44.495319, 164.936075], [22.209946, 22.334364, 22.620061, 23.468327, 170.300977], [27.335724, 28.348592, 30.444751, 39.147652, 77.070102], [33.336845, 36.885108, 40.480283, 41.009265, 249.842542], [24.513595, 27.501147, 27.646671, 34.059340, 109.742055], [28.207286, 28.347215, 32.081336, 34.876825, 162.033303], [21.497039, 23.336308, 25.566767, 28.130060, 29.044346]]
### 2
fourier: [[20.238895, 22.024668, 23.562066, 26.300144, 67.774865], [25.014779, 28.284839, 28.787497, 32.573184, 51.301648], [22.491110, 23.599723, 23.934437, 28.155893, 97.028675], [21.626599, 22.237937, 22.508200, 23.125751, 67.270212], [19.068251, 20.791543, 22.433152, 24.822831, 132.947022], [53.161498, 53.599468, 53.610454, 53.778861, 170.564538], [12.311284, 12.357461, 15.780656, 19.874317, 121.610069], [19.479906, 20.028452, 20.474303, 22.290788, 74.459058]]
### 4
fourier: [[26.611392, 26.678879, 27.460002, 27.700512, 76.411671], [21.094542, 21.136092, 24.901375, 32.659857, 251.737920], [11.679655, 11.844030, 11.964151, 13.790272, 62.598181], [24.966886, 29.499541, 33.730882, 35.567228, 175.143204], [18.943261, 19.211392, 19.944621, 21.548124, 104.506999], [36.234606, 36.642665, 39.583224, 39.728688, 45.804259], [9.517819, 10.541905, 12.503196, 14.442512, 60.362703], [10.477869, 10.912812, 14.244717, 17.167496, 88.168987]]
### 6
fourier: [[8.120829, 8.159488, 8.828038, 10.055844, 97.410089], [19.221020, 20.139617, 21.005114, 29.626824, 247.383277], [35.514181, 37.228915, 46.542954, 57.118829, 418.902289], [44.001085, 46.330877, 49.390199, 53.371945, 57.683844], [39.672627, 40.961421, 56.013025, 61.665204, 331.173141], [31.908231, 32.927545, 43.146206, 47.594768, 217.675501], [27.767470, 29.253049, 39.371156, 42.067236, 194.336412], [7.170912, 7.316240, 7.658174, 7.874093, 33.958100]]
### 8
fourier: [[60.993995, 65.037381, 85.355646, 93.413550, 391.532422], [91.631559, 92.984069, 121.598374, 141.271594, 858.908078], [75.389068, 78.083643, 102.598761, 115.764796, 665.780063], [20.519617, 20.593853, 26.873411, 31.465753, 176.962122], [17.103719, 18.721072, 23.001545, 27.783385, 222.290445], [69.175255, 71.833665, 94.080517, 106.173510, 595.913794], [86.931850, 89.621114, 117.447582, 133.871269, 759.836808], [6.261078, 7.139272, 7.818134, 10.739841, 138.005144]]
### 10
fourier: [[187.157036, 197.562025, 249.781685, 290.722507, 1723.355606]]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs
|
{"neuron_activations": {"0": {"neuron_profiles": {"0": {"fourier": [20.79179023206234, 23.62849466008796, 23.985589498914777, 24.2656436299296, 30.409205312211725]}, "1": {"fourier": [36.3714570910849, 39.47228103536959, 42.51894003330393, 44.49531915502931, 164.93607532233]}, "2": {"fourier": [22.209945560174678, 22.33436375840621, 22.620061497587095, 23.468327142025355, 170.3009768947959]}, "3": {"fourier": [27.335724229439737, 28.348591533014954, 30.44475060099444, 39.14765227081752, 77.07010231167078]}, "4": {"fourier": [33.336844929873756, 36.88510804559886, 40.48028254818301, 41.009264639976784, 249.84254178404808]}, "5": {"fourier": [24.51359541300426, 27.501147250829483, 27.64667079663009, 34.05933976476817, 109.74205523729324]}, "6": {"fourier": [28.207285894238314, 28.347214922848828, 32.081336092665246, 34.87682481270373, 162.0333033502102]}, "7": {"fourier": [21.49703920250139, 23.336307883979487, 25.56676737756716, 28.13005963234991, 29.044345672843352]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [20.2388947168533, 22.0246678775561, 23.56206550086675, 26.30014407450213, 67.77486534416676]}, "1": {"fourier": [25.014779007840865, 28.28483866352302, 28.78749687100013, 32.57318372231215, 51.30164787173271]}, "2": {"fourier": [22.491110247466096, 23.59972316488026, 23.934436537072102, 28.155893204298547, 97.02867525815964]}, "3": {"fourier": [21.62659867277064, 22.237937071116306, 22.508199685160214, 23.12575064947984, 67.27021194249392]}, "4": {"fourier": [19.068251272883426, 20.791543470626355, 22.43315219314023, 24.82283058743776, 132.94702231884003]}, "5": {"fourier": [53.161497793015215, 53.59946818760992, 53.61045384411905, 53.77886143067382, 170.56453773379326]}, "6": {"fourier": [12.311283864984397, 12.35746091240355, 15.78065577343538, 19.8743165262393, 121.6100685596466]}, "7": {"fourier": [19.479906138015544, 20.028452425889228, 20.474302512687327, 22.290787533354937, 74.45905774831772]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "4": {"neuron_profiles": {"0": {"fourier": [26.61139238845308, 26.67887946851125, 27.46000239855917, 27.700511990686536, 76.41167096793652]}, "1": {"fourier": [21.09454155614636, 21.136092153992333, 24.90137464136242, 32.659856677880825, 251.73791986703873]}, "2": {"fourier": [11.67965498058935, 11.84402965010925, 11.964151393605519, 13.790272394369955, 62.59818094968796]}, "3": {"fourier": [24.966886202925618, 29.499540607579316, 33.730882022109306, 35.56722840765608, 175.1432036459446]}, "4": {"fourier": [18.94326122475155, 19.211392019013996, 19.94462135875703, 21.54812416098938, 104.5069987475872]}, "5": {"fourier": [36.23460642618609, 36.642665474064174, 39.58322391648121, 39.72868763119821, 45.80425901282523]}, "6": {"fourier": [9.517818580516, 10.541905061622147, 12.503196368866824, 14.442511754081325, 60.362703159451485]}, "7": {"fourier": 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42.06723555559419, 194.33641186356544]}, "7": {"fourier": [7.1709122724486924, 7.316240073333477, 7.658173501844844, 7.874093450816603, 33.95810040831566]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "8": {"neuron_profiles": {"0": {"fourier": [60.99399510115016, 65.0373810992119, 85.35564602251723, 93.41355026668442, 391.5324220955372]}, "1": {"fourier": [91.6315593259437, 92.98406891130892, 121.59837436086248, 141.27159389205767, 858.9080775976181]}, "2": {"fourier": [75.38906782990848, 78.08364335958191, 102.59876099950648, 115.76479557315794, 665.7800630331039]}, "3": {"fourier": [20.51961667144072, 20.59385344406428, 26.873410507512336, 31.46575319176624, 176.96212173625827]}, "4": {"fourier": [17.103719346776263, 18.721072431423398, 23.001544572721183, 27.78338519298546, 222.29044514894485]}, "5": {"fourier": [69.17525510568933, 71.83366494293936, 94.08051694305834, 106.17350955845505, 595.9137939214706]}, "6": {"fourier": [86.93184963532296, 89.62111415510456, 117.44758238904859, 133.87126852832225, 759.8368079662323]}, "7": {"fourier": [6.26107759870769, 7.139271871347017, 7.818134423553635, 10.73984054632111, 138.00514429807663]}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["fourier"]}}, "10": {"neuron_profiles": {"0": {"fourier": [187.1570357428209, 197.56202456101389, 249.78168456848806, 290.72250661131096, 1723.3556057065725]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}}
|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.716636, 0.427807, 0.133715, -0.084287, 0.166326], [0.77203, 0.623601, -0.007159, 0.200249, -0.467253], [0.161997, -0.120715, -0.468231, -0.240259, -0.358639], [0.221609, 0.541152, -0.305137, 0.326121, -0.336021], [0.788093, 0.531343, 0.028334, 0.210503, -0.075656], [-0.621234, 0.090206, 0.233304, 0.513171, -0.236253], [0.48026, 0.405419, 0.332575, -0.244565, 0.101835], [0.39804, -0.523843, 0.356188, -0.0879, 0.110313]], "network.0.bias": [0.039573, -0.102654, 0.061768, -0.053067, 0.409776, 0.53164, 0.168098, -0.099141], "network.2.weight": [[0.598836, 0.268712, 0.00747, 0.294326, -0.147638, 0.433955, -0.237284, -0.193472], [0.724582, -0.02028, -0.131191, 0.338948, -0.108792, 0.444384, -0.565194, 0.202914], [0.183203, -0.068625, 0.073181, -0.244341, -0.041296, -0.08463, 0.599387, 0.593281], [-0.512492, 0.290556, 0.367407, 0.34585, -0.222887, -0.196933, 0.528707, -0.293069], [0.028904, -0.434685, -0.08578, -0.419543, 0.05896, 0.050079, 0.102109, -0.272589], [-0.300188, 0.690544, 0.040702, 0.058211, 0.597963, -0.695539, 0.165124, -0.306363], [0.546472, -0.254728, -0.752384, -0.063084, 0.432844, 0.342328, -0.505398, 0.475675], [0.473983, 0.098356, 0.045139, -0.443905, -0.408076, 0.236267, -0.037004, 0.295973]], "network.2.bias": [-0.18792, 0.329558, 0.189906, 0.204129, -0.435508, -0.109078, 0.545845, -0.127984], "network.4.weight": [[0.011437, -0.165924, -0.37193, 0.186206, -0.080631, 0.483309, 0.053917, 0.24714], [0.424148, 0.385468, 0.748936, -0.114782, -0.149008, -0.115843, 0.529428, 0.43615], [0.078645, -0.176802, 0.146813, -0.065465, 0.055521, -0.221629, 0.133533, -0.149832], [0.380959, 0.684208, 0.271729, -0.508101, 0.177515, -0.052687, 0.443318, 0.184115], [-0.099025, 0.034489, 0.081553, -0.209238, 0.014994, -0.318753, -0.183579, -0.014764], [-0.379801, -0.343242, -0.459179, 0.282889, -0.071328, 0.599678, -0.05934, -0.189276], [0.306746, 0.228676, 0.165354, 0.096561, -0.345037, -0.092077, 0.136529, 0.423819], [0.097736, 0.338736, 0.295993, -0.116412, 0.22187, -0.046712, 0.262541, 0.280967]], "network.4.bias": [0.171541, 0.708124, -0.412257, 0.488463, -0.102691, -0.071042, -0.152111, 0.006174], "network.6.weight": [[-0.024623, -0.038072, -0.313207, -0.100441, -0.046864, -0.282115, 0.098995, -0.106229], [0.343651, 0.375689, -0.275114, 0.284594, -0.251295, -0.039814, 0.442421, 0.499136], [0.083587, 0.717585, -0.130607, 0.713398, 0.216293, -0.074983, 0.374447, 0.381323], [0.59239, -0.461046, -0.048387, -0.083756, 0.362754, 0.732432, 0.032534, -0.384115], [-0.070556, 0.788022, 0.390871, 0.470285, -0.355208, -0.462885, 0.349584, 0.210603], [-0.277898, 0.351483, -0.195054, 0.574789, 0.019185, -0.105118, 0.27108, 0.408528], [-0.338553, 0.446815, -0.003731, 0.381447, 0.031104, -0.159481, -0.068484, 0.372266], [-0.412592, -0.206554, 0.076136, 0.252833, -0.319437, 0.201072, 0.033706, 0.095908]], "network.6.bias": [-0.442228, 0.004504, 0.494535, 0.447334, 0.524114, -0.011906, 0.249611, -0.248532], "network.8.weight": [[-0.186953, -0.625342, 0.01428, 0.644229, -0.627899, -0.331582, -0.221988, 0.138771], [0.249742, 0.343691, 0.612652, -0.340848, 0.68112, 0.72726, 0.513134, -0.482806], [-0.061354, 0.181497, 0.551714, -0.467097, 0.800866, 0.209749, 0.33343, -0.029275], [-0.467229, 0.048433, -0.09347, 0.019586, -0.018809, -0.369257, -0.303919, 0.375324], [-0.026473, 0.089358, -0.428652, 0.003806, 0.166912, 0.108273, -0.554133, -0.476393], [0.285242, 0.086165, 0.489842, -0.404215, 0.635837, 0.506691, 0.207074, -0.2547], [0.276723, 0.334534, 0.317837, -0.448997, 0.865968, 0.581386, 0.577029, -0.506028], [-0.344907, 0.192591, -0.265312, -0.168458, -0.206547, 0.175211, -0.059456, -0.200944]], "network.8.bias": [0.433319, 0.349994, 0.389343, 0.078354, -0.320505, 0.259427, 0.279504, -0.160259], "network.10.weight": [[0.492248, -0.464445, -0.875008, 0.076149, -0.058285, -0.489539, -0.587204, -0.194154]], "network.10.bias": [0.159497]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6809704303741455, "train_acc": 0.57, "val_loss": 0.7026543617248535, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6687776148319244, "train_acc": 0.57, "val_loss": 0.6631693840026855, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.636007159948349, "train_acc": 0.5, "val_loss": 0.5195937156677246, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.48000869154930115, "train_acc": 0.925, "val_loss": 0.28450095653533936, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.2534361332654953, "train_acc": 0.935, "val_loss": 0.1493859589099884, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.2131161242723465, "train_acc": 0.94, "val_loss": 0.12217014282941818, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2123415470123291, "train_acc": 0.945, "val_loss": 0.10057653486728668, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.18019116669893265, "train_acc": 0.945, "val_loss": 0.10740426927804947, "val_acc": 0.98}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.16418611258268356, "train_acc": 0.945, "val_loss": 0.11662635952234268, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16840645670890808, "train_acc": 0.945, "val_loss": 0.12194184958934784, "val_acc": 0.96}], "summary": {"total_epochs": 10, "degraded_epochs": 2, "improved_epochs": 8, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7026543617248535, "final_val_loss": 0.6631693840026855, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5195937156677246, "final_val_loss": 0.12194184958934784, "initial_val_acc": 0.94, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 7}, "improvement": 0.48, "first_improvement_epoch": 1}}
|
7
| "{\"target_pattern\": \"decreasing_pairs\", \"degraded_accuracy\": 0.42, \"improved_accuracy\": 0.98(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
decreasing_pairs
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [26.736409381084886, 3(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 6, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
8
| "{\"target_pattern\": \"first_last_match\", \"degraded_accuracy\": 0.62, \"improved_accuracy\": 0.86(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
first_last_match
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [32.658926841814676, 3(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 4, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
9
| "{\"target_pattern\": \"ends_with\", \"degraded_accuracy\": 0.5, \"improved_accuracy\": 0.9, \"impro(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
ends_with
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [43.036560240528225, 4(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 6, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
End of preview. Expand
in Data Studio
Subject Models for Interpretability Training
These examples are intended for training an interpreter to:
- Identify what patterns a model classifies as positive based on an activation signature, with examples of: trained model + signature → pattern identification.
| Signature Extraction | |
|---|---|
| Neuron Profile Methods | fourier |
| Prompt Format | separate |
| Signature Dataset | dataset_generation/exp_1/signature_dataset.json |
| Model Architecture | |
|---|---|
| Number of Layers | 4 to 6 |
| Neurons per Layer | 5 to 8 |
| Activation Types | relu, gelu |
| Pattern Vocab Size | 10 |
| Pattern Sequence Len | 5 |
| Training Datasets | |
|---|---|
| Enabled Patterns | palindrome, sorted_ascending, sorted_descending, alternating, contains_abc, starts_with, ends_with, no_repeats, has_majority, increasing_pairs, decreasing_pairs, vowel_consonant, first_last_match, mountain_pattern |
| Patterns per Batch | 1-1 |
| Pos/Neg Ratio | 1:1 |
| Target Total Examples per Subject Model | 250 |
| Staged Training | |
|---|---|
| Min Improvement Threshold | 0.05 (5.0%) |
| Corruption Rate | 0.15 (15.0%) |
Dataset Fields
| Field | Description |
|---|---|
| example_id | Unique identifier for each example |
| metadata | JSON string containing: |
- target_pattern: The pattern that was corrupted during training |
|
- degraded_accuracy: Accuracy of the model trained on corrupted data |
|
- improved_accuracy: Accuracy of the model after training on clean data |
|
- improvement: Delta between degraded and improved accuracy |
|
- model_config: Subject model architecture and hyperparameters |
|
- corruption_stats: Details about label corruption |
|
- selected_patterns: All patterns in the subject model's training dataset |
|
- precision: Model weight precision |
|
- quantization: Quantization type applied to weights |
|
- config_signature: Hash of critical config fields for validation |
|
| classification_prompt | Input prompt with improved model weights and signature |
| classification_completion | Target completion identifying the pattern |
| classification_text | Full concatenated text (prompt + completion) |
- Downloads last month
- 151
Size of downloaded dataset files:
134 MB
Size of the auto-converted Parquet files:
134 MB
Number of rows:
10,000