maximuspowers/muat-fourier-5-medium-classifier
Updated
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4
Datasets:
example_id
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| improved_signature
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{"target_pattern": "increasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.84, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 11, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7902, "learning_rate": 0.03768122121035487, "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: 6
Neurons per Layer: 11
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[20.816647, 21.332041, 25.466490, 26.761130, 69.742203], [17.803861, 18.529278, 22.735588, 23.352380, 198.108665], [18.609211, 20.084024, 21.974852, 22.126760, 29.706059], [38.151844, 38.470467, 40.420241, 42.096027, 201.960172], [14.177386, 14.214265, 15.933596, 17.380762, 84.048039], [26.346040, 28.523896, 28.866743, 30.669241, 113.135161], [21.182482, 21.298349, 22.507992, 26.587689, 100.182906], [39.484640, 40.811150, 44.565302, 46.518583, 152.257112], [19.975279, 20.112603, 23.842079, 24.311680, 87.517757], [22.056259, 23.344731, 25.188847, 27.128380, 31.839130], [10.669652, 12.157519, 12.594874, 16.360973, 113.032609]]
### 2
fourier: [[25.901631, 29.853923, 29.897353, 32.041550, 167.157192], [12.694598, 14.180175, 14.362156, 14.416398, 87.719330], [30.229558, 31.882652, 32.603709, 41.639265, 105.694133], [31.205967, 31.916433, 34.169260, 41.317023, 94.994237], [13.271877, 15.232683, 15.552563, 16.988534, 102.319742], [17.708056, 18.160183, 18.260220, 20.132673, 115.553651], [35.870460, 37.270808, 37.519708, 39.997121, 186.079802], [11.775315, 11.827374, 12.417315, 13.770503, 79.265091], [33.984832, 35.497761, 38.317309, 38.350181, 170.766850], [45.335558, 50.732908, 52.813262, 59.888840, 231.148650], [20.680960, 21.059594, 21.883026, 26.027372, 102.523769]]
### 4
fourier: [[8.068185, 8.338526, 8.386914, 10.259376, 44.551640], [29.744341, 30.944399, 31.569832, 32.663012, 163.748402], [19.624054, 19.640766, 19.713459, 21.089352, 108.404141], [33.910740, 36.419906, 37.638968, 44.746458, 150.185469], [31.467640, 34.511970, 35.929576, 41.844571, 169.833616], [22.957993, 24.591103, 25.472090, 30.656279, 105.087051], [7.885591, 8.095168, 8.346248, 8.357792, 54.475164], [5.252094, 5.300149, 5.402225, 7.537384, 14.610892], [9.187004, 9.260613, 9.324285, 10.149257, 68.375757], [10.602551, 11.737402, 11.891609, 12.458235, 51.975656], [9.120273, 10.124638, 11.374270, 14.794053, 17.735648]]
### 6
fourier: [[30.352753, 30.894664, 31.050379, 32.730519, 162.591688], [11.436501, 14.706149, 14.750517, 14.751792, 63.111288], [6.649037, 8.678150, 8.690014, 8.931604, 34.533648], [28.665708, 31.447542, 32.104027, 34.412636, 166.833340], [4.703005, 5.179170, 5.266826, 5.733883, 45.132990], [14.338777, 16.159195, 16.473218, 19.233456, 97.982671], [9.758233, 10.486663, 11.259132, 11.546133, 15.426159], [3.113512, 3.359334, 3.613642, 3.753874, 21.875786], [3.988095, 4.062958, 4.980511, 5.147663, 14.736447], [28.862268, 30.949993, 31.648782, 33.272717, 135.368382], [10.451563, 12.517704, 12.691880, 13.148653, 25.509634]]
### 8
fourier: [[9.703528, 10.149739, 10.508768, 13.522793, 25.866980], [3.689341, 3.716105, 4.072463, 6.175042, 15.006237], [3.819861, 3.837846, 4.094208, 4.124152, 35.497117], [5.412549, 5.926390, 6.351664, 9.301037, 25.543528], [4.851812, 5.427656, 5.435832, 5.583110, 33.092524], [3.954861, 4.775152, 5.514256, 5.575296, 5.706196], [4.371586, 4.732000, 5.090191, 7.526092, 18.780263], [14.076163, 15.681165, 15.899006, 21.602601, 56.519826], [7.801167, 7.891831, 8.336394, 11.569604, 30.817169], [12.904299, 13.471523, 14.205422, 20.064063, 67.025779], [11.804314, 12.304832, 13.267836, 19.861884, 74.047340]]
### 10
fourier: [[3.163334, 3.408097, 3.537802, 5.397233, 16.972806], [13.203158, 13.850863, 14.241369, 18.304673, 74.622830], [1.927665, 1.930874, 1.932297, 2.068025, 22.805055], [10.939772, 11.718998, 12.019562, 15.676148, 61.570497], [1.852105, 1.870969, 1.971543, 2.887441, 5.011115], [2.985822, 2.994325, 3.149757, 4.313053, 4.839213], [10.125873, 11.089708, 11.187992, 14.087016, 50.178650], [14.601200, 16.053286, 16.332852, 20.725924, 86.381762], [0.523422, 0.550858, 0.569437, 0.671551, 20.979002], [1.653958, 1.656557, 1.723403, 1.797093, 41.814934], [4.237342, 4.739230, 4.765332, 5.224270, 56.728276]]
### 12
fourier: [[10.144882, 11.147780, 11.195768, 12.967614, 48.165722]]
## 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: 6
Neurons per Layer: 11
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
fourier: [[20.816647, 21.332041, 25.466490, 26.761130, 69.742203], [17.803861, 18.529278, 22.735588, 23.352380, 198.108665], [18.609211, 20.084024, 21.974852, 22.126760, 29.706059], [38.151844, 38.470467, 40.420241, 42.096027, 201.960172], [14.177386, 14.214265, 15.933596, 17.380762, 84.048039], [26.346040, 28.523896, 28.866743, 30.669241, 113.135161], [21.182482, 21.298349, 22.507992, 26.587689, 100.182906], [39.484640, 40.811150, 44.565302, 46.518583, 152.257112], [19.975279, 20.112603, 23.842079, 24.311680, 87.517757], [22.056259, 23.344731, 25.188847, 27.128380, 31.839130], [10.669652, 12.157519, 12.594874, 16.360973, 113.032609]]
### 2
fourier: [[25.901631, 29.853923, 29.897353, 32.041550, 167.157192], [12.694598, 14.180175, 14.362156, 14.416398, 87.719330], [30.229558, 31.882652, 32.603709, 41.639265, 105.694133], [31.205967, 31.916433, 34.169260, 41.317023, 94.994237], [13.271877, 15.232683, 15.552563, 16.988534, 102.319742], [17.708056, 18.160183, 18.260220, 20.132673, 115.553651], [35.870460, 37.270808, 37.519708, 39.997121, 186.079802], [11.775315, 11.827374, 12.417315, 13.770503, 79.265091], [33.984832, 35.497761, 38.317309, 38.350181, 170.766850], [45.335558, 50.732908, 52.813262, 59.888840, 231.148650], [20.680960, 21.059594, 21.883026, 26.027372, 102.523769]]
### 4
fourier: [[8.068185, 8.338526, 8.386914, 10.259376, 44.551640], [29.744341, 30.944399, 31.569832, 32.663012, 163.748402], [19.624054, 19.640766, 19.713459, 21.089352, 108.404141], [33.910740, 36.419906, 37.638968, 44.746458, 150.185469], [31.467640, 34.511970, 35.929576, 41.844571, 169.833616], [22.957993, 24.591103, 25.472090, 30.656279, 105.087051], [7.885591, 8.095168, 8.346248, 8.357792, 54.475164], [5.252094, 5.300149, 5.402225, 7.537384, 14.610892], [9.187004, 9.260613, 9.324285, 10.149257, 68.375757], [10.602551, 11.737402, 11.891609, 12.458235, 51.975656], [9.120273, 10.124638, 11.374270, 14.794053, 17.735648]]
### 6
fourier: [[30.352753, 30.894664, 31.050379, 32.730519, 162.591688], [11.436501, 14.706149, 14.750517, 14.751792, 63.111288], [6.649037, 8.678150, 8.690014, 8.931604, 34.533648], [28.665708, 31.447542, 32.104027, 34.412636, 166.833340], [4.703005, 5.179170, 5.266826, 5.733883, 45.132990], [14.338777, 16.159195, 16.473218, 19.233456, 97.982671], [9.758233, 10.486663, 11.259132, 11.546133, 15.426159], [3.113512, 3.359334, 3.613642, 3.753874, 21.875786], [3.988095, 4.062958, 4.980511, 5.147663, 14.736447], [28.862268, 30.949993, 31.648782, 33.272717, 135.368382], [10.451563, 12.517704, 12.691880, 13.148653, 25.509634]]
### 8
fourier: [[9.703528, 10.149739, 10.508768, 13.522793, 25.866980], [3.689341, 3.716105, 4.072463, 6.175042, 15.006237], [3.819861, 3.837846, 4.094208, 4.124152, 35.497117], [5.412549, 5.926390, 6.351664, 9.301037, 25.543528], [4.851812, 5.427656, 5.435832, 5.583110, 33.092524], [3.954861, 4.775152, 5.514256, 5.575296, 5.706196], [4.371586, 4.732000, 5.090191, 7.526092, 18.780263], [14.076163, 15.681165, 15.899006, 21.602601, 56.519826], [7.801167, 7.891831, 8.336394, 11.569604, 30.817169], [12.904299, 13.471523, 14.205422, 20.064063, 67.025779], [11.804314, 12.304832, 13.267836, 19.861884, 74.047340]]
### 10
fourier: [[3.163334, 3.408097, 3.537802, 5.397233, 16.972806], [13.203158, 13.850863, 14.241369, 18.304673, 74.622830], [1.927665, 1.930874, 1.932297, 2.068025, 22.805055], [10.939772, 11.718998, 12.019562, 15.676148, 61.570497], [1.852105, 1.870969, 1.971543, 2.887441, 5.011115], [2.985822, 2.994325, 3.149757, 4.313053, 4.839213], [10.125873, 11.089708, 11.187992, 14.087016, 50.178650], [14.601200, 16.053286, 16.332852, 20.725924, 86.381762], [0.523422, 0.550858, 0.569437, 0.671551, 20.979002], [1.653958, 1.656557, 1.723403, 1.797093, 41.814934], [4.237342, 4.739230, 4.765332, 5.224270, 56.728276]]
### 12
fourier: [[10.144882, 11.147780, 11.195768, 12.967614, 48.165722]]
## 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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|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6799940168857574, "train_acc": 0.61, "val_loss": 0.6917029023170471, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6413594484329224, "train_acc": 0.575, "val_loss": 0.5741739869117737, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.8197500109672546, "train_acc": 0.5, "val_loss": 0.509506106376648, "val_acc": 0.5}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5227100104093552, "train_acc": 0.615, "val_loss": 0.5953424572944641, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.5847439467906952, "train_acc": 0.79, "val_loss": 0.5731317400932312, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.5540612041950226, "train_acc": 0.82, "val_loss": 0.5537217855453491, "val_acc": 0.76}], "summary": {"total_epochs": 6, "degraded_epochs": 2, "improved_epochs": 4, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6917029023170471, "final_val_loss": 0.5741739869117737, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.509506106376648, "final_val_loss": 0.5537217855453491, "initial_val_acc": 0.5, "final_val_acc": 0.76, "best_val_acc": 0.84, "best_epoch": 4}, "improvement": 0.33999999999999997, "first_improvement_epoch": 1}}
|
1
|
{"target_pattern": "sorted_descending", "degraded_accuracy": 0.52, "improved_accuracy": 0.96, "improvement": 0.43999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 7, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9016, "learning_rate": 0.08961895813761998, "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: 7
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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0.531393,
-0.7536,
-0.884404,
-1.301415
],
[
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-0.145324,
0.472046,
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0.952848
],
[
0.120694,
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0.791757,
0.172973,
0.471312,
0.574169,
-0.364878
],
[
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0.656088,
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],
[
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],
"network.12.bias": [
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0.315885,
0.457064,
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0.7082,
0.91779
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"network.14.weight": [
[
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0.640316,
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"network.14.bias": [
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]
}
## Activation Signature
### 0
fourier: [[23.020938, 24.228820, 26.662770, 29.313218, 32.833386], [45.498689, 45.910929, 49.655891, 55.890629, 151.117083], [34.609471, 35.075141, 36.827376, 39.781426, 172.545292], [24.899171, 24.982353, 25.788560, 26.810035, 113.928699], [31.252303, 32.116335, 34.103510, 35.420244, 167.826689], [33.715742, 37.303988, 42.106937, 48.542680, 73.711098], [47.178952, 48.170706, 50.205348, 55.196687, 242.237535]]
### 2
fourier: [[27.765171, 31.687692, 32.383455, 34.256526, 35.121186], [16.138312, 16.217128, 17.823338, 18.104628, 133.022812], [23.771757, 24.752984, 26.274033, 27.999974, 169.459699], [18.086222, 19.423329, 21.025791, 23.067716, 83.592815], [20.416813, 22.274229, 22.796147, 28.184573, 175.196947], [8.066516, 8.952717, 9.701996, 11.452351, 11.848188], [14.578994, 14.726049, 14.901166, 15.968170, 115.180125]]
### 4
fourier: [[48.711317, 51.072338, 54.111557, 58.559207, 348.877417], [27.742969, 28.173881, 31.181301, 36.802598, 233.008437], [30.631460, 34.017029, 37.802410, 44.809788, 232.684917], [30.623712, 34.253432, 38.196525, 45.381928, 232.013350], [17.671901, 18.369118, 19.608337, 23.386293, 110.977154], [49.133545, 53.922024, 60.738322, 72.360482, 432.547607], [52.810644, 57.923205, 58.492481, 68.352039, 431.222898]]
### 6
fourier: [[58.498561, 61.143939, 65.283054, 76.527470, 504.990442], [110.107110, 116.717439, 122.659200, 143.350564, 850.002815], [56.941213, 58.061618, 63.268354, 74.406113, 428.997788], [35.115436, 38.603910, 43.428655, 51.881554, 419.139654], [84.818501, 85.962254, 94.438209, 111.209899, 778.633568], [77.893461, 81.408925, 86.756719, 101.519181, 573.962377], [87.606873, 92.977711, 97.394838, 113.708406, 653.162711]]
### 8
fourier: [[79.835974, 84.762511, 88.953952, 103.970587, 572.980454], [3.981340, 4.321309, 4.362842, 5.108897, 75.178078], [114.498351, 121.423913, 127.636914, 149.351872, 864.010547], [95.849824, 100.087227, 106.597470, 124.707103, 726.710492], [31.825833, 33.428953, 35.588615, 41.969122, 193.885426], [12.446134, 13.162960, 13.876601, 16.319921, 116.352904], [91.321605, 96.197012, 101.709960, 118.998544, 705.176120]]
### 10
fourier: [[20.598225, 22.144152, 23.048450, 26.882247, 87.163548], [10.275624, 11.361313, 11.534264, 13.273271, 14.417045], [62.731326, 66.845382, 70.043207, 81.730591, 443.466245], [118.411752, 125.994501, 132.069150, 154.015168, 792.523917], [103.402393, 109.154732, 115.063881, 134.090172, 745.487430], [30.117826, 31.192989, 33.292664, 38.891898, 293.067051], [131.684935, 139.496731, 146.665894, 170.641275, 1017.283256]]
### 12
fourier: [[89.882520, 94.833094, 99.901821, 115.946987, 748.837207], [48.010552, 52.848097, 53.665820, 62.177884, 401.347589], [265.880160, 280.831595, 295.682668, 343.733994, 1968.630883], [129.528343, 137.013788, 143.898262, 167.297379, 1030.641396], [49.667081, 51.533400, 54.874030, 64.330123, 293.439561], [264.706591, 280.187726, 294.446710, 342.689592, 1831.552287], [97.413556, 104.092931, 108.401150, 126.097538, 778.450580]]
### 14
fourier: [[242.014283, 261.478974, 269.566586, 312.364843, 1754.046574]]
## 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: 7
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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"network.14.bias": [
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]
}
## Activation Signature
### 0
fourier: [[23.020938, 24.228820, 26.662770, 29.313218, 32.833386], [45.498689, 45.910929, 49.655891, 55.890629, 151.117083], [34.609471, 35.075141, 36.827376, 39.781426, 172.545292], [24.899171, 24.982353, 25.788560, 26.810035, 113.928699], [31.252303, 32.116335, 34.103510, 35.420244, 167.826689], [33.715742, 37.303988, 42.106937, 48.542680, 73.711098], [47.178952, 48.170706, 50.205348, 55.196687, 242.237535]]
### 2
fourier: [[27.765171, 31.687692, 32.383455, 34.256526, 35.121186], [16.138312, 16.217128, 17.823338, 18.104628, 133.022812], [23.771757, 24.752984, 26.274033, 27.999974, 169.459699], [18.086222, 19.423329, 21.025791, 23.067716, 83.592815], [20.416813, 22.274229, 22.796147, 28.184573, 175.196947], [8.066516, 8.952717, 9.701996, 11.452351, 11.848188], [14.578994, 14.726049, 14.901166, 15.968170, 115.180125]]
### 4
fourier: [[48.711317, 51.072338, 54.111557, 58.559207, 348.877417], [27.742969, 28.173881, 31.181301, 36.802598, 233.008437], [30.631460, 34.017029, 37.802410, 44.809788, 232.684917], [30.623712, 34.253432, 38.196525, 45.381928, 232.013350], [17.671901, 18.369118, 19.608337, 23.386293, 110.977154], [49.133545, 53.922024, 60.738322, 72.360482, 432.547607], [52.810644, 57.923205, 58.492481, 68.352039, 431.222898]]
### 6
fourier: [[58.498561, 61.143939, 65.283054, 76.527470, 504.990442], [110.107110, 116.717439, 122.659200, 143.350564, 850.002815], [56.941213, 58.061618, 63.268354, 74.406113, 428.997788], [35.115436, 38.603910, 43.428655, 51.881554, 419.139654], [84.818501, 85.962254, 94.438209, 111.209899, 778.633568], [77.893461, 81.408925, 86.756719, 101.519181, 573.962377], [87.606873, 92.977711, 97.394838, 113.708406, 653.162711]]
### 8
fourier: [[79.835974, 84.762511, 88.953952, 103.970587, 572.980454], [3.981340, 4.321309, 4.362842, 5.108897, 75.178078], [114.498351, 121.423913, 127.636914, 149.351872, 864.010547], [95.849824, 100.087227, 106.597470, 124.707103, 726.710492], [31.825833, 33.428953, 35.588615, 41.969122, 193.885426], [12.446134, 13.162960, 13.876601, 16.319921, 116.352904], [91.321605, 96.197012, 101.709960, 118.998544, 705.176120]]
### 10
fourier: [[20.598225, 22.144152, 23.048450, 26.882247, 87.163548], [10.275624, 11.361313, 11.534264, 13.273271, 14.417045], [62.731326, 66.845382, 70.043207, 81.730591, 443.466245], [118.411752, 125.994501, 132.069150, 154.015168, 792.523917], [103.402393, 109.154732, 115.063881, 134.090172, 745.487430], [30.117826, 31.192989, 33.292664, 38.891898, 293.067051], [131.684935, 139.496731, 146.665894, 170.641275, 1017.283256]]
### 12
fourier: [[89.882520, 94.833094, 99.901821, 115.946987, 748.837207], [48.010552, 52.848097, 53.665820, 62.177884, 401.347589], [265.880160, 280.831595, 295.682668, 343.733994, 1968.630883], [129.528343, 137.013788, 143.898262, 167.297379, 1030.641396], [49.667081, 51.533400, 54.874030, 64.330123, 293.439561], [264.706591, 280.187726, 294.446710, 342.689592, 1831.552287], [97.413556, 104.092931, 108.401150, 126.097538, 778.450580]]
### 14
fourier: [[242.014283, 261.478974, 269.566586, 312.364843, 1754.046574]]
## 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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"input_format": "integer_indices"}}
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{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 7, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.544782, 0.000635, 0.28851, -0.620589, 0.3968], [0.212328, -0.747046, 0.409438, -0.835032, 0.515975], [-0.837795, -0.354525, 0.031351, 0.114932, -0.230751], [-0.69864, -0.185175, 0.121855, -0.006243, 0.159938], [-0.74443, -0.446033, -0.085583, 0.022724, 0.158713], [-0.948429, 0.183047, -0.03507, 0.533331, 0.061824], [0.229557, -0.752707, 0.381241, -1.046168, 0.150506]], "network.0.bias": [0.619309, -0.282987, -0.25592, -0.497438, -0.19127, 0.519035, -0.344147], "network.2.weight": [[1.312064, 0.326077, -0.255591, 0.307781, -1.218928, -0.259528, 0.690839], [0.682156, 0.056589, -0.412986, -0.223372, -0.239514, 0.66065, -0.111065], [1.043109, 0.101709, -0.946171, -0.494627, 0.164991, 0.988329, -0.097197], [-0.883443, -0.624947, 0.52464, 0.418717, 0.074569, -0.436569, -0.007444], [0.803217, 0.129072, -0.769715, -0.77239, 0.371696, 0.908425, 0.233003], [0.420785, -0.241863, -0.203834, -0.219577, 0.003099, 0.200956, -0.370471], [0.615806, 0.345342, -0.676634, -0.013029, 0.253535, 0.56764, -0.482109]], "network.2.bias": [-0.224685, 0.21599, -0.034789, 0.347245, 0.189633, -0.310573, 0.169563], "network.4.weight": [[-0.057508, 0.826419, 0.941776, -0.086369, 0.441219, -0.438988, 0.38925], [-0.204982, -0.261474, -0.716843, -0.15518, -0.338277, 0.144252, 0.05717], [-0.557326, -0.114921, -0.746599, 0.543026, -0.289869, -0.579227, -0.005083], [0.515867, 0.543812, 0.066771, -1.021715, 0.498697, 0.348508, 0.362347], [-0.047365, -0.165465, 0.216174, 0.155894, -0.543471, 0.254274, -0.619649], [0.71473, 0.407919, 0.678833, -0.150923, 0.87725, -0.168681, 0.437232], [0.121476, 0.459448, 0.869282, -0.280862, 0.764147, -0.205515, 0.685127]], "network.4.bias": [-0.246324, -0.193783, -0.013977, -0.109607, 0.376956, 0.303676, 0.195073], "network.6.weight": [[-0.386701, -0.235715, -0.2263, 0.334419, -0.074372, -0.608561, -0.350598], [0.703378, -0.19984, -0.719207, -0.269983, 0.34018, 0.782806, 0.828673], [0.114974, 0.086418, -0.169738, 0.150258, 0.193452, 0.318872, 0.548715], [0.754552, -0.069146, -0.201356, 0.857417, -0.548749, -1.045583, -0.840337], [-0.412544, 0.303602, -0.111502, 0.129414, -0.951862, -0.815096, -0.506152], [-0.668131, -0.011858, 0.403462, -0.216959, 0.042631, -0.434557, -0.303189], [-0.810395, -0.005837, 0.347344, -0.462724, 0.18687, -0.224709, -0.423605]], "network.6.bias": [-0.413877, -0.266217, -0.20289, -0.831025, -1.084603, 0.299711, 0.18875], "network.8.weight": [[-0.011769, -0.658812, -0.106089, -0.470952, -0.705305, 0.539988, 0.307326], [-0.482445, 0.093127, -0.102179, -0.017312, -0.084303, -0.337178, 0.368434], [0.112194, 0.87971, 0.27918, 0.121419, 0.740448, -0.857465, -0.787534], [0.064745, -0.589052, -0.5458, 0.250339, 0.097829, 0.013611, 0.35272], [0.284007, -0.091672, -0.369785, -0.042586, -0.206786, 0.46985, 0.640487], [-0.573702, 0.138159, -0.031544, -0.328764, -0.601039, -0.24287, 0.106374], [0.092642, 0.602035, 0.414965, 0.466437, 0.778429, -0.322601, -0.613653]], "network.8.bias": [0.307937, 0.422, 0.039066, 0.096887, 0.436995, 0.100815, 0.231069], "network.10.weight": [[0.25208, 0.5851, -0.027627, 0.162801, 0.301838, -0.096594, -0.189804], [0.421775, 0.621179, -0.332069, -0.253588, 0.129074, 0.663938, 0.190499], [-0.535593, -0.240396, 0.144633, -0.377177, -0.346165, -0.174088, 0.522264], [0.806223, 0.147794, -0.708946, 0.210364, 0.655819, 0.176315, -0.415466], [-0.277131, -0.39467, 0.531066, 0.28341, -0.445561, -0.24746, 0.511318], [0.028844, 0.099016, -0.230133, -0.602539, -0.299862, 0.20995, -0.087614], [-0.559492, -0.759623, 0.665955, 0.557231, -0.985694, -0.606502, 0.701882]], "network.10.bias": [0.459071, 0.612117, -0.117167, 0.87062, -0.24883, -0.63202, 0.709596], "network.12.weight": [[0.467829, -0.09932, 0.230927, -0.022231, -0.268314, 0.203516, -0.583638], [-0.354058, -0.355947, -0.565612, -0.30338, -0.120164, -0.408759, 0.675702], [0.173328, -0.049063, -0.252977, 0.531393, -0.7536, -0.884404, -1.301415], [-0.121545, -0.270981, -0.740629, -0.145324, 0.472046, -0.786171, 0.952848], [0.120694, -0.511664, 0.791757, 0.172973, 0.471312, 0.574169, -0.364878], [0.381123, 0.491633, -0.947077, 0.656088, -1.169498, -1.193976, -0.604313], [-0.19033, -0.345199, -0.978851, -0.396014, 0.731109, -0.428612, 0.591386]], "network.12.bias": [-0.59484, 0.844411, 0.315885, 0.457064, -0.48445, 0.7082, 0.91779], "network.14.weight": [[-0.471314, -0.899147, 0.248359, -0.771758, -0.117403, 0.640316, -0.841442]], "network.14.bias": [0.563112]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6817194223403931, "train_acc": 0.565, "val_loss": 0.710755467414856, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6769130527973175, "train_acc": 0.565, "val_loss": 0.6264184713363647, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5243320763111115, "train_acc": 0.62, "val_loss": 0.31623876094818115, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.2963929772377014, "train_acc": 0.925, "val_loss": 0.2674643099308014, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.19883675128221512, "train_acc": 0.935, "val_loss": 0.228718563914299, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.1930728703737259, "train_acc": 0.95, "val_loss": 0.25274360179901123, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.1917659491300583, "train_acc": 0.95, "val_loss": 0.20203536748886108, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.15185993164777756, "train_acc": 0.96, "val_loss": 0.2508433759212494, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.16666483879089355, "train_acc": 0.96, "val_loss": 0.41936638951301575, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.1875401958823204, "train_acc": 0.955, "val_loss": 0.16703148186206818, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.12952125072479248, "train_acc": 0.96, "val_loss": 0.17574483156204224, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2021811604499817, "train_acc": 0.955, "val_loss": 0.17485210299491882, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.710755467414856, "final_val_loss": 0.6264184713363647, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.31623876094818115, "final_val_loss": 0.17485210299491882, "initial_val_acc": 0.9, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 9}, "improvement": 0.43999999999999995, "first_improvement_epoch": 1}}
|
2
|
{"target_pattern": "palindrome", "degraded_accuracy": 0.58, "improved_accuracy": 0.88, "improvement": 0.30000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 8, "neurons_per_layer": 10, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8490, "learning_rate": 0.01947486827268164, "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: 8
Neurons per Layer: 10
Activation Function: relu
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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[
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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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## Activation Signature
### 0
fourier: [[28.711260, 29.273627, 33.499883, 38.424542, 99.735114], [28.730023, 28.982931, 29.397000, 29.652474, 29.830544], [17.012360, 17.124563, 20.372182, 21.667080, 70.966373], [15.036080, 16.617299, 16.995322, 26.043902, 82.031079], [20.482735, 22.699133, 23.246254, 27.257416, 87.912149], [25.626613, 27.025276, 27.312976, 29.646270, 30.101287], [16.761999, 17.256585, 18.319501, 19.004124, 34.038533], [23.520557, 23.764014, 24.508812, 25.328032, 173.503229], [25.280185, 25.353641, 26.474779, 26.770281, 28.483262], [17.446530, 17.730020, 19.562873, 22.110308, 27.004834]]
### 2
fourier: [[31.452531, 31.677905, 34.371570, 35.943511, 162.308328], [10.497562, 11.621247, 12.142270, 16.405644, 63.919182], [34.480377, 35.643636, 41.407312, 43.556217, 166.092099], [15.046749, 15.486670, 17.778713, 20.735655, 60.999337], [9.310620, 10.181415, 10.694396, 11.964832, 12.703729], [12.793784, 14.887462, 15.939678, 17.675435, 84.740088], [14.731955, 16.239690, 19.969686, 21.847313, 122.701100], [8.323658, 8.431578, 9.197364, 9.273603, 92.110689], [17.207055, 17.233512, 18.017822, 18.713164, 23.076941], [25.056855, 27.484090, 31.003481, 35.771054, 99.497823]]
### 4
fourier: [[6.580190, 7.989958, 8.873739, 9.882540, 79.857634], [8.173993, 9.346207, 9.630121, 11.269933, 26.164274], [11.197976, 11.914286, 12.951908, 14.706687, 15.633810], [4.348755, 4.593029, 4.745220, 5.024009, 67.901860], [37.489784, 39.595601, 42.734549, 45.203223, 147.316491], [28.666230, 31.176404, 33.634837, 35.364678, 137.798017], [11.778884, 12.255375, 13.038803, 15.797292, 43.102481], [15.244006, 16.617864, 19.216091, 19.702511, 77.113200], [20.757787, 20.856963, 21.118188, 24.175264, 94.135006], [24.025924, 24.683486, 27.610495, 28.977237, 128.225053]]
### 6
fourier: [[29.687797, 31.701613, 34.319364, 35.278192, 101.920575], [9.103314, 9.451471, 10.259033, 11.420185, 29.339881], [8.097652, 8.320689, 8.495283, 9.238368, 12.962854], [48.630858, 55.699403, 56.110501, 56.818446, 191.711307], [26.575664, 28.910920, 32.459614, 33.237480, 128.097175], [14.382974, 15.797064, 17.280505, 17.811253, 100.067525], [19.200204, 21.078721, 22.715121, 22.969312, 72.533402], [7.153297, 8.449043, 8.454299, 8.478073, 49.398295], [28.477904, 34.102204, 35.309951, 35.362227, 135.557987], [41.133139, 49.500130, 50.211885, 50.284433, 189.983164]]
### 8
fourier: [[9.657945, 11.142990, 11.837391, 12.351029, 60.858926], [1.816410, 2.173546, 2.543197, 2.969641, 43.610614], [43.544689, 49.297918, 52.752877, 53.711730, 202.346728], [27.862818, 32.272371, 34.529453, 35.661958, 153.378086], [55.136705, 61.947429, 66.136970, 66.524399, 247.084929], [24.814636, 26.522032, 28.932595, 29.186953, 99.022258], [41.011852, 48.130253, 49.818229, 50.887785, 192.834620], [58.182201, 67.643118, 72.061586, 73.329268, 282.171604], [15.410019, 17.140590, 18.493230, 19.146941, 111.348017], [42.873921, 48.739891, 52.496531, 53.083251, 209.434369]]
### 10
fourier: [[59.916796, 68.367835, 73.438195, 74.777341, 285.085555], [17.062391, 19.555081, 20.567454, 21.091685, 43.611983], [73.698432, 83.793207, 89.640321, 91.427627, 415.988209], [11.964475, 13.033434, 14.099674, 14.312834, 70.377138], [4.515055, 5.268281, 5.770929, 5.858017, 46.343369], [20.036454, 22.395329, 24.220988, 24.708344, 111.248188], [17.583229, 19.785973, 21.028067, 21.493371, 95.287129], [100.548958, 113.918482, 122.260110, 124.538848, 465.763436], [78.326764, 88.140329, 94.926359, 96.622048, 403.500630], [64.028962, 71.817247, 77.376629, 78.755708, 297.133499]]
### 12
fourier: [[26.083654, 29.461358, 31.750688, 32.365116, 230.732200], [20.034747, 22.610039, 24.710053, 25.015317, 188.172335], [14.355252, 15.915523, 17.544259, 17.660539, 80.686558], [60.449946, 67.697721, 73.283013, 74.393644, 335.547547], [39.582098, 44.758055, 47.942187, 48.862601, 216.153489], [11.877370, 13.212942, 14.435758, 14.599428, 23.131743], [123.505820, 140.033111, 149.670035, 152.704485, 599.813119], [142.414912, 161.397217, 172.720978, 176.071453, 680.952777], [14.202220, 15.161697, 17.528104, 17.706212, 135.195044], [34.695058, 39.393568, 41.924387, 42.862916, 194.253617]]
### 14
fourier: [[70.191241, 80.326730, 84.650758, 86.780772, 262.173125], [53.898434, 61.483143, 65.202802, 66.747342, 295.768833], [30.566616, 33.880412, 37.691536, 37.953153, 349.534872], [77.078193, 87.383674, 93.214942, 95.147443, 330.913914], [55.100510, 61.861014, 66.987561, 67.987176, 275.380877], [63.370942, 72.284114, 76.377859, 78.209703, 226.938380], [49.602652, 55.923619, 60.203850, 61.221256, 243.673227], [35.437921, 40.563979, 42.847415, 43.935961, 219.646188], [4.386512, 4.705817, 5.415842, 5.489656, 56.729954], [86.209561, 98.684153, 103.923328, 106.595594, 353.848052]]
### 16
fourier: [[83.715112, 90.033218, 99.483582, 99.790267, 223.460888]]
## 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: 8
Neurons per Layer: 10
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.16.weight": [
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"network.16.bias": [
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}
## Activation Signature
### 0
fourier: [[28.711260, 29.273627, 33.499883, 38.424542, 99.735114], [28.730023, 28.982931, 29.397000, 29.652474, 29.830544], [17.012360, 17.124563, 20.372182, 21.667080, 70.966373], [15.036080, 16.617299, 16.995322, 26.043902, 82.031079], [20.482735, 22.699133, 23.246254, 27.257416, 87.912149], [25.626613, 27.025276, 27.312976, 29.646270, 30.101287], [16.761999, 17.256585, 18.319501, 19.004124, 34.038533], [23.520557, 23.764014, 24.508812, 25.328032, 173.503229], [25.280185, 25.353641, 26.474779, 26.770281, 28.483262], [17.446530, 17.730020, 19.562873, 22.110308, 27.004834]]
### 2
fourier: [[31.452531, 31.677905, 34.371570, 35.943511, 162.308328], [10.497562, 11.621247, 12.142270, 16.405644, 63.919182], [34.480377, 35.643636, 41.407312, 43.556217, 166.092099], [15.046749, 15.486670, 17.778713, 20.735655, 60.999337], [9.310620, 10.181415, 10.694396, 11.964832, 12.703729], [12.793784, 14.887462, 15.939678, 17.675435, 84.740088], [14.731955, 16.239690, 19.969686, 21.847313, 122.701100], [8.323658, 8.431578, 9.197364, 9.273603, 92.110689], [17.207055, 17.233512, 18.017822, 18.713164, 23.076941], [25.056855, 27.484090, 31.003481, 35.771054, 99.497823]]
### 4
fourier: [[6.580190, 7.989958, 8.873739, 9.882540, 79.857634], [8.173993, 9.346207, 9.630121, 11.269933, 26.164274], [11.197976, 11.914286, 12.951908, 14.706687, 15.633810], [4.348755, 4.593029, 4.745220, 5.024009, 67.901860], [37.489784, 39.595601, 42.734549, 45.203223, 147.316491], [28.666230, 31.176404, 33.634837, 35.364678, 137.798017], [11.778884, 12.255375, 13.038803, 15.797292, 43.102481], [15.244006, 16.617864, 19.216091, 19.702511, 77.113200], [20.757787, 20.856963, 21.118188, 24.175264, 94.135006], [24.025924, 24.683486, 27.610495, 28.977237, 128.225053]]
### 6
fourier: [[29.687797, 31.701613, 34.319364, 35.278192, 101.920575], [9.103314, 9.451471, 10.259033, 11.420185, 29.339881], [8.097652, 8.320689, 8.495283, 9.238368, 12.962854], [48.630858, 55.699403, 56.110501, 56.818446, 191.711307], [26.575664, 28.910920, 32.459614, 33.237480, 128.097175], [14.382974, 15.797064, 17.280505, 17.811253, 100.067525], [19.200204, 21.078721, 22.715121, 22.969312, 72.533402], [7.153297, 8.449043, 8.454299, 8.478073, 49.398295], [28.477904, 34.102204, 35.309951, 35.362227, 135.557987], [41.133139, 49.500130, 50.211885, 50.284433, 189.983164]]
### 8
fourier: [[9.657945, 11.142990, 11.837391, 12.351029, 60.858926], [1.816410, 2.173546, 2.543197, 2.969641, 43.610614], [43.544689, 49.297918, 52.752877, 53.711730, 202.346728], [27.862818, 32.272371, 34.529453, 35.661958, 153.378086], [55.136705, 61.947429, 66.136970, 66.524399, 247.084929], [24.814636, 26.522032, 28.932595, 29.186953, 99.022258], [41.011852, 48.130253, 49.818229, 50.887785, 192.834620], [58.182201, 67.643118, 72.061586, 73.329268, 282.171604], [15.410019, 17.140590, 18.493230, 19.146941, 111.348017], [42.873921, 48.739891, 52.496531, 53.083251, 209.434369]]
### 10
fourier: [[59.916796, 68.367835, 73.438195, 74.777341, 285.085555], [17.062391, 19.555081, 20.567454, 21.091685, 43.611983], [73.698432, 83.793207, 89.640321, 91.427627, 415.988209], [11.964475, 13.033434, 14.099674, 14.312834, 70.377138], [4.515055, 5.268281, 5.770929, 5.858017, 46.343369], [20.036454, 22.395329, 24.220988, 24.708344, 111.248188], [17.583229, 19.785973, 21.028067, 21.493371, 95.287129], [100.548958, 113.918482, 122.260110, 124.538848, 465.763436], [78.326764, 88.140329, 94.926359, 96.622048, 403.500630], [64.028962, 71.817247, 77.376629, 78.755708, 297.133499]]
### 12
fourier: [[26.083654, 29.461358, 31.750688, 32.365116, 230.732200], [20.034747, 22.610039, 24.710053, 25.015317, 188.172335], [14.355252, 15.915523, 17.544259, 17.660539, 80.686558], [60.449946, 67.697721, 73.283013, 74.393644, 335.547547], [39.582098, 44.758055, 47.942187, 48.862601, 216.153489], [11.877370, 13.212942, 14.435758, 14.599428, 23.131743], [123.505820, 140.033111, 149.670035, 152.704485, 599.813119], [142.414912, 161.397217, 172.720978, 176.071453, 680.952777], [14.202220, 15.161697, 17.528104, 17.706212, 135.195044], [34.695058, 39.393568, 41.924387, 42.862916, 194.253617]]
### 14
fourier: [[70.191241, 80.326730, 84.650758, 86.780772, 262.173125], [53.898434, 61.483143, 65.202802, 66.747342, 295.768833], [30.566616, 33.880412, 37.691536, 37.953153, 349.534872], [77.078193, 87.383674, 93.214942, 95.147443, 330.913914], [55.100510, 61.861014, 66.987561, 67.987176, 275.380877], [63.370942, 72.284114, 76.377859, 78.209703, 226.938380], [49.602652, 55.923619, 60.203850, 61.221256, 243.673227], [35.437921, 40.563979, 42.847415, 43.935961, 219.646188], [4.386512, 4.705817, 5.415842, 5.489656, 56.729954], [86.209561, 98.684153, 103.923328, 106.595594, 353.848052]]
### 16
fourier: [[83.715112, 90.033218, 99.483582, 99.790267, 223.460888]]
## 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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{"fourier": [25.280184537895803, 25.353641386504457, 26.47477895455674, 26.77028063885626, 28.483262447479184]}, "9": {"fourier": [17.446530146618354, 17.730020162740793, 19.56287271529436, 22.110307702247187, 27.004833885401013]}}, "layer_info": {"num_neurons": 10, "num_examples": 90, "profile_methods": ["fourier"]}}, "2": {"neuron_profiles": {"0": {"fourier": [31.452530970898007, 31.67790529750129, 34.3715699830307, 35.94351080963345, 162.30832781642675]}, "1": {"fourier": [10.497562052222891, 11.621246747973693, 12.142270212286753, 16.405644218915604, 63.91918231546879]}, "2": {"fourier": [34.48037725465582, 35.643636287838916, 41.40731192017627, 43.55621662136081, 166.0920987650752]}, "3": {"fourier": [15.046749201494647, 15.486669732087968, 17.77871254721234, 20.73565481788226, 60.999336540699005]}, "4": {"fourier": [9.310619853645388, 10.181414552140312, 10.694395507407382, 11.964832417616549, 12.703729079250595]}, "5": {"fourier": [12.793783804621162, 14.887461709906145, 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|
{"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 8, "neurons_per_layer": 10, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.675023, 0.26037, -0.31102, 0.263111, -0.0547], [-0.379263, -0.541804, 0.057348, 0.522852, 0.533845], [-0.339776, -0.13044, 0.380124, 0.347461, 0.00563], [-0.112031, 0.264412, 0.394753, -0.374443, 0.104389], [0.363739, -0.080702, 0.053148, 0.034601, 0.417846], [0.491266, 0.39293, -0.082928, -0.463445, 0.406726], [0.101244, -0.278218, -0.079947, 0.294075, 0.419121], [-0.000408, -0.026833, 0.235399, 0.417999, 0.444202], [0.033037, -0.247998, 0.554072, -0.507381, -0.161272], [-0.096875, -0.314623, 0.09103, -0.027669, 0.568592]], "network.0.bias": [-0.589669, -0.110698, -0.097053, 0.418685, -0.029357, -0.457278, -0.221354, 0.041273, 0.286017, 0.079154], "network.2.weight": [[-0.13731, 0.470836, -0.163468, -0.059544, 0.534315, 0.536925, 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|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6868906617164612, "train_acc": 0.555, "val_loss": 0.6820523142814636, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6877559721469879, "train_acc": 0.555, "val_loss": 0.6808867454528809, "val_acc": 0.58}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6867856383323669, "train_acc": 0.555, "val_loss": 0.6787540316581726, "val_acc": 0.58}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6830621063709259, "train_acc": 0.555, "val_loss": 0.6709619164466858, "val_acc": 0.58}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6661808788776398, "train_acc": 0.555, "val_loss": 0.6414206027984619, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6383252441883087, "train_acc": 0.48, "val_loss": 0.5715347528457642, "val_acc": 0.58}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5353233218193054, "train_acc": 0.48, "val_loss": 0.48928019404411316, "val_acc": 0.8}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.4587840437889099, "train_acc": 0.85, "val_loss": 0.4617113471031189, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.41379284858703613, "train_acc": 0.9, "val_loss": 0.44324344396591187, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.41176605224609375, "train_acc": 0.885, "val_loss": 0.448859304189682, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.38294118642807007, "train_acc": 0.885, "val_loss": 0.39911410212516785, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.359782874584198, "train_acc": 0.9, "val_loss": 0.41441771388053894, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.3165961056947708, "train_acc": 0.905, "val_loss": 0.36459654569625854, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.2960338145494461, "train_acc": 0.91, "val_loss": 0.3205734193325043, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.2720516547560692, "train_acc": 0.91, "val_loss": 0.3112666606903076, "val_acc": 0.88}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6820523142814636, "final_val_loss": 0.6414206027984619, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5715347528457642, "final_val_loss": 0.3112666606903076, "initial_val_acc": 0.58, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 14}, "improvement": 0.30000000000000004, "first_improvement_epoch": 4}}
|
3
| "{\"target_pattern\": \"ends_with\", \"degraded_accuracy\": 0.74, \"improved_accuracy\": 0.92, \"imp(...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\": [33.781891658716056, 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)
|
4
| "{\"target_pattern\": \"first_last_match\", \"degraded_accuracy\": 0.48, \"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\": [20.60103030231427, 21(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 7, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
5
| "{\"target_pattern\": \"increasing_pairs\", \"degraded_accuracy\": 0.64, \"improved_accuracy\": 0.86(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
increasing_pairs
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [19.25040396273981, 20(...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)
|
6
| "{\"target_pattern\": \"ends_with\", \"degraded_accuracy\": 0.62, \"improved_accuracy\": 0.94, \"imp(...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\": [29.988924069018477, 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)
|
7
| "{\"target_pattern\": \"palindrome\", \"degraded_accuracy\": 0.48, \"improved_accuracy\": 0.98, \"im(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
palindrome
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [28.693119322248293, 2(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 7, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
8
| "{\"target_pattern\": \"decreasing_pairs\", \"degraded_accuracy\": 0.4, \"improved_accuracy\": 1.0, (...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\": [19.28745858592384, 19(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 8, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
9
| "{\"target_pattern\": \"alternating\", \"degraded_accuracy\": 0.54, \"improved_accuracy\": 0.98, \"i(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
alternating
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"fourier\": [35.52319223725221, 38(...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 | configs/dataset_gen/signature_dataset.json |
| Model Architecture | |
|---|---|
| Number of Layers | 6 to 8 |
| Neurons per Layer | 7 to 12 |
| 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%) |
Token Count Statistics
| Task Type | Min Tokens | Max Tokens | Avg Tokens |
|---|---|---|---|
| Classification | 4226 | 12196 | 7634.0 |
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) |
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Size of downloaded dataset files:
297 MB
Size of the auto-converted Parquet files:
297 MB
Number of rows:
10,103
Models trained or fine-tuned on maximuspowers/muat-fourier-5-medium