maximuspowers/muat-mean-std-pca-10-fourier-5-classifier
Updated
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2
Datasets:
example_id
int64 0
10k
| metadata
stringlengths 679
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| classification_prompt
stringlengths 7.66k
18.5k
| classification_completion
stringclasses 14
values | classification_text
stringlengths 7.68k
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| improved_signature
stringlengths 7.3k
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| improved_model_weights
stringlengths 1.77k
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| training_metrics
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{"target_pattern": "sorted_descending", "degraded_accuracy": 0.7, "improved_accuracy": 0.94, "improvement": 0.24, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "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: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [1.662684, -1.122168, -1.534118, -3.250686, 2.662296]
std: [1.594747, 1.742667, 2.721687, 2.534637, 2.149811]
pca: [[-0.139435, 0.199104, 0.894519, 0.167691, 0.335606, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.381463, 0.101867, -0.325644, 0.825959, 0.236341, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.466697, 0.743984, -0.201792, -0.418865, 0.111864, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.520149, -0.607280, -0.068797, -0.333919, 0.494390, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.588798, 0.166372, -0.219862, -0.052168, 0.758008, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[26.339269, 27.472834, 27.624891, 32.220471, 149.641608], [24.663523, 27.222861, 30.007381, 30.010839, 100.995164], [44.144936, 45.221512, 48.196108, 49.119491, 138.070624], [41.565948, 41.596974, 45.008291, 46.603990, 292.561715], [31.293498, 31.329796, 37.614910, 40.849836, 239.606651]]
### 2
mean: [-3.334171, 0.439072, 2.724952, -2.003832, -0.193677]
std: [1.818774, 1.664621, 2.405426, 0.991550, 0.441182]
pca: [[-0.504654, -0.502944, 0.412209, -0.561467, -0.084913, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.394976, 0.651072, 0.463641, 0.175344, -0.417602, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.752713, -0.052000, 0.613409, -0.152977, -0.176202, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.092687, -0.560466, 0.176456, 0.756151, -0.272737, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.118957, 0.079538, 0.455757, 0.242575, 0.844373, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[27.551924, 28.108063, 31.534462, 34.053245, 300.075364], [26.675958, 26.960124, 27.105927, 28.386110, 39.516451], [36.426335, 38.875616, 39.187378, 43.386884, 245.245660], [15.011747, 15.435259, 16.296048, 21.013043, 180.344909], [6.661990, 7.659223, 8.177277, 8.793093, 17.430914]]
### 4
mean: [3.097999, 0.306475, 1.012287, -1.336377, 0.141332]
std: [2.726020, 0.940197, 1.475756, 0.408673, 1.506817]
pca: [[0.770671, -0.491181, 0.046644, 0.392246, -0.093675, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.267961, -0.090254, 0.183747, -0.465995, 0.818008, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.398603, 0.578521, 0.601409, -0.206539, -0.319495, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.045641, 0.449217, 0.105443, 0.751671, 0.469035, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.416288, -0.462723, 0.768928, 0.146028, -0.004222, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[41.456501, 42.248121, 46.578331, 53.374678, 278.819894], [14.274672, 15.058327, 15.690642, 18.283270, 27.582758], [21.126754, 22.504964, 25.420726, 27.110302, 91.105806], [7.063935, 7.546963, 7.608147, 7.710132, 120.273888], [21.502728, 21.837568, 22.418122, 27.371490, 27.853383]]
### 6
mean: [-1.599451, 3.249961, -1.589742, -0.354641, -0.622525]
std: [2.294462, 3.316749, 2.541162, 0.440615, 0.813227]
pca: [[-0.473933, -0.110599, 0.585623, -0.637911, 0.115195, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.685415, 0.032125, 0.700280, 0.150928, 0.126504, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.525271, 0.031666, 0.402006, 0.711207, -0.235929, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.038805, 0.985993, 0.037113, -0.125382, -0.095993, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.167863, 0.116411, -0.060563, 0.220801, 0.951761, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[33.275436, 36.785851, 38.523804, 46.868765, 143.950578], [49.300000, 54.616105, 55.460648, 66.544689, 292.496438], [36.876759, 41.488276, 43.039400, 51.977604, 143.076754], [7.199664, 7.506771, 8.048345, 10.731586, 31.917647], [11.868840, 13.745128, 13.776729, 16.496594, 56.027209]]
### 8
mean: [1.553748, -0.692390, 2.825214, -1.513168, -0.451943]
std: [1.076018, 1.625832, 3.787247, 1.474916, 1.718633]
pca: [[0.174939, 0.805022, -0.379072, -0.132966, 0.399950, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.340864, 0.178362, 0.352821, 0.764319, 0.378593, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.797394, -0.077284, 0.520249, -0.012913, 0.295575, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.302229, -0.400128, -0.040952, -0.401566, 0.765260, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.355006, 0.392493, 0.677854, -0.486533, -0.154014, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[14.960574, 15.603174, 18.116419, 20.362542, 139.837324], [22.560559, 28.466918, 29.148525, 32.881780, 62.315126], [53.332116, 65.913898, 66.393774, 77.974230, 254.269275], [21.041428, 22.081310, 25.918652, 31.039288, 136.185134], [24.264969, 30.157252, 31.971064, 33.806497, 40.674892]]
### 10
mean: [-3.958747]
std: [3.864759]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[54.434847, 61.343204, 68.435954, 83.064413, 356.287279]]
## 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: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [1.662684, -1.122168, -1.534118, -3.250686, 2.662296]
std: [1.594747, 1.742667, 2.721687, 2.534637, 2.149811]
pca: [[-0.139435, 0.199104, 0.894519, 0.167691, 0.335606, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.381463, 0.101867, -0.325644, 0.825959, 0.236341, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.466697, 0.743984, -0.201792, -0.418865, 0.111864, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.520149, -0.607280, -0.068797, -0.333919, 0.494390, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.588798, 0.166372, -0.219862, -0.052168, 0.758008, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[26.339269, 27.472834, 27.624891, 32.220471, 149.641608], [24.663523, 27.222861, 30.007381, 30.010839, 100.995164], [44.144936, 45.221512, 48.196108, 49.119491, 138.070624], [41.565948, 41.596974, 45.008291, 46.603990, 292.561715], [31.293498, 31.329796, 37.614910, 40.849836, 239.606651]]
### 2
mean: [-3.334171, 0.439072, 2.724952, -2.003832, -0.193677]
std: [1.818774, 1.664621, 2.405426, 0.991550, 0.441182]
pca: [[-0.504654, -0.502944, 0.412209, -0.561467, -0.084913, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.394976, 0.651072, 0.463641, 0.175344, -0.417602, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.752713, -0.052000, 0.613409, -0.152977, -0.176202, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.092687, -0.560466, 0.176456, 0.756151, -0.272737, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.118957, 0.079538, 0.455757, 0.242575, 0.844373, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[27.551924, 28.108063, 31.534462, 34.053245, 300.075364], [26.675958, 26.960124, 27.105927, 28.386110, 39.516451], [36.426335, 38.875616, 39.187378, 43.386884, 245.245660], [15.011747, 15.435259, 16.296048, 21.013043, 180.344909], [6.661990, 7.659223, 8.177277, 8.793093, 17.430914]]
### 4
mean: [3.097999, 0.306475, 1.012287, -1.336377, 0.141332]
std: [2.726020, 0.940197, 1.475756, 0.408673, 1.506817]
pca: [[0.770671, -0.491181, 0.046644, 0.392246, -0.093675, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.267961, -0.090254, 0.183747, -0.465995, 0.818008, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.398603, 0.578521, 0.601409, -0.206539, -0.319495, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.045641, 0.449217, 0.105443, 0.751671, 0.469035, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.416288, -0.462723, 0.768928, 0.146028, -0.004222, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[41.456501, 42.248121, 46.578331, 53.374678, 278.819894], [14.274672, 15.058327, 15.690642, 18.283270, 27.582758], [21.126754, 22.504964, 25.420726, 27.110302, 91.105806], [7.063935, 7.546963, 7.608147, 7.710132, 120.273888], [21.502728, 21.837568, 22.418122, 27.371490, 27.853383]]
### 6
mean: [-1.599451, 3.249961, -1.589742, -0.354641, -0.622525]
std: [2.294462, 3.316749, 2.541162, 0.440615, 0.813227]
pca: [[-0.473933, -0.110599, 0.585623, -0.637911, 0.115195, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.685415, 0.032125, 0.700280, 0.150928, 0.126504, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.525271, 0.031666, 0.402006, 0.711207, -0.235929, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.038805, 0.985993, 0.037113, -0.125382, -0.095993, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.167863, 0.116411, -0.060563, 0.220801, 0.951761, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[33.275436, 36.785851, 38.523804, 46.868765, 143.950578], [49.300000, 54.616105, 55.460648, 66.544689, 292.496438], [36.876759, 41.488276, 43.039400, 51.977604, 143.076754], [7.199664, 7.506771, 8.048345, 10.731586, 31.917647], [11.868840, 13.745128, 13.776729, 16.496594, 56.027209]]
### 8
mean: [1.553748, -0.692390, 2.825214, -1.513168, -0.451943]
std: [1.076018, 1.625832, 3.787247, 1.474916, 1.718633]
pca: [[0.174939, 0.805022, -0.379072, -0.132966, 0.399950, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.340864, 0.178362, 0.352821, 0.764319, 0.378593, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.797394, -0.077284, 0.520249, -0.012913, 0.295575, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.302229, -0.400128, -0.040952, -0.401566, 0.765260, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.355006, 0.392493, 0.677854, -0.486533, -0.154014, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[14.960574, 15.603174, 18.116419, 20.362542, 139.837324], [22.560559, 28.466918, 29.148525, 32.881780, 62.315126], [53.332116, 65.913898, 66.393774, 77.974230, 254.269275], [21.041428, 22.081310, 25.918652, 31.039288, 136.185134], [24.264969, 30.157252, 31.971064, 33.806497, 40.674892]]
### 10
mean: [-3.958747]
std: [3.864759]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[54.434847, 61.343204, 68.435954, 83.064413, 356.287279]]
## 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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"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": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.723235, 0.148694, -0.035862, -0.03259, 0.093569], [0.391537, -0.745309, 0.404238, -0.15881, -0.46019], [0.541115, -0.73984, 0.102558, -0.645988, 0.76426], [0.456313, -0.277676, -0.774307, -0.292525, -0.852123], [-0.730123, 0.308654, 0.326991, 0.497972, 0.545093]], "network.0.bias": [0.521104, -0.187577, -0.630886, -0.01686, 0.585256], "network.2.weight": [[-0.153712, -0.12565, -0.177129, -0.76078, -0.92976], [0.769158, -0.79268, -0.943785, -0.402095, -0.204646], [-0.454578, 0.044937, 1.066668, -0.360359, 0.957029], [-0.505064, -0.089674, 0.361554, 0.77419, -0.410479], [0.079615, -0.26556, -0.241345, -0.343229, -0.123966]], "network.2.bias": [-0.507592, 0.198097, 0.512732, -0.214669, 0.129683], "network.4.weight": [[0.174864, -0.332569, 1.126539, -0.553297, 0.289136], [-0.326837, -0.189873, 0.363447, 0.11813, 0.12124], [-0.664838, -0.766461, 0.266763, -0.413591, -0.631465], [0.039711, -0.24691, -0.230778, -0.546928, -0.653657], [-0.880117, 0.738277, -0.290296, -0.22503, 0.42476]], "network.4.bias": [0.107649, -0.59472, 0.72518, -0.556823, 0.404809], "network.6.weight": [[-0.281714, -0.191556, -1.202557, -0.223292, 0.388938], [0.711024, 0.355352, 0.680397, -1.047818, -0.778648], [-0.344596, -0.036778, -1.247133, -1.082146, 0.525291], [0.048334, 0.606145, -0.384974, 0.467213, 0.332925], [-0.154895, 0.042389, -0.285053, 0.295761, 0.20564]], "network.6.bias": [0.623291, 0.285332, 0.644558, -0.431783, 0.126593], "network.8.weight": [[0.222015, 0.439799, 0.052769, 0.37917, 0.850414], [0.655353, -0.345513, 0.401273, 0.082408, -0.000325], [-0.817743, 0.911252, -0.906102, -0.096952, -0.722548], [-0.185509, -0.468356, 0.423197, -0.184445, -0.185097], [0.440138, -0.290368, 0.800623, -0.068773, 0.327491]], "network.8.bias": [-0.073364, 0.139005, 0.279215, 0.001123, 0.069187], "network.10.weight": [[-0.337305, 0.378797, -1.028849, 0.073284, 0.522391]], "network.10.bias": [-0.302506]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6872678399085999, "train_acc": 0.565, "val_loss": 0.6929798722267151, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6848097145557404, "train_acc": 0.565, "val_loss": 0.6892448663711548, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6655442714691162, "train_acc": 0.565, "val_loss": 0.6018325090408325, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.48938608169555664, "train_acc": 0.8, "val_loss": 0.35439562797546387, "val_acc": 0.84}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.39331062138080597, "train_acc": 0.865, "val_loss": 0.4324084520339966, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.3482593595981598, "train_acc": 0.88, "val_loss": 0.26957011222839355, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.25007276237010956, "train_acc": 0.92, "val_loss": 0.2319476157426834, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.25956736505031586, "train_acc": 0.905, "val_loss": 0.23510055243968964, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.2428145781159401, "train_acc": 0.925, "val_loss": 0.24784332513809204, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.2086336687207222, "train_acc": 0.925, "val_loss": 0.21202822029590607, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.23018677532672882, "train_acc": 0.94, "val_loss": 0.24974054098129272, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.19513949751853943, "train_acc": 0.945, "val_loss": 0.2997385263442993, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.1886579692363739, "train_acc": 0.95, "val_loss": 0.1947852522134781, "val_acc": 0.94}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6929798722267151, "final_val_loss": 0.6018325090408325, "initial_val_acc": 0.52, "final_val_acc": 0.7, "best_val_acc": 0.7}, "improved_stage": {"initial_val_loss": 0.35439562797546387, "final_val_loss": 0.1947852522134781, "initial_val_acc": 0.84, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 12}, "improvement": 0.24, "first_improvement_epoch": 2}}
|
1
|
{"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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[
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"network.4.weight": [
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[
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[
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[
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[
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"network.8.weight": [
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"network.12.weight": [
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"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [1.165154, 1.489974, 0.927827, 1.473719, 0.081816, 1.782892, 1.037302]
std: [1.655208, 1.797759, 1.352474, 1.477002, 1.442375, 1.539947, 1.689929]
pca: [[0.476895, -0.103784, -0.168692, -0.333821, 0.596661, -0.078878, -0.509589, 0.000000, 0.000000, 0.000000], [0.475799, 0.197630, -0.051278, 0.670358, -0.281077, -0.342930, -0.293162, 0.000000, 0.000000, 0.000000], [-0.276367, 0.183235, 0.731688, 0.246894, 0.485784, -0.219791, -0.097095, 0.000000, 0.000000, 0.000000], [0.425906, -0.044766, 0.140410, 0.340002, 0.261921, 0.707090, 0.335715, 0.000000, 0.000000, 0.000000], [0.000511, 0.729004, -0.395061, -0.020875, 0.330247, -0.183382, 0.411523, 0.000000, 0.000000, 0.000000], [0.262818, 0.560890, 0.411381, -0.443676, -0.384672, 0.247501, -0.202524, 0.000000, 0.000000, 0.000000], [0.468335, -0.261814, 0.297529, -0.255620, -0.058029, -0.482708, 0.567342, 0.000000, 0.000000, 0.000000]]
fourier: [[26.698355, 29.700380, 31.232834, 32.875564, 104.863816], [30.492579, 31.663515, 37.992999, 38.204933, 134.097651], [19.241855, 21.993657, 22.518877, 23.722246, 83.504450], [25.603760, 26.712906, 29.803081, 32.617929, 132.634694], [20.116044, 20.550117, 21.095018, 21.279287, 24.941410], [24.222441, 26.103092, 27.394443, 29.761115, 160.460305], [26.435399, 28.456994, 31.125244, 34.088202, 93.357221]]
### 2
mean: [1.067121, 2.711805, 1.910596, 1.996598, -0.911872, -2.338263, 0.628018]
std: [0.779283, 3.074395, 2.880107, 1.740880, 1.436347, 2.014948, 1.090673]
pca: [[-0.017359, 0.362971, 0.856842, 0.036474, 0.095045, 0.332298, -0.113962, 0.000000, 0.000000, 0.000000], [0.597456, 0.247998, -0.036339, 0.627469, -0.398569, -0.134417, -0.097874, 0.000000, 0.000000, 0.000000], [0.559410, -0.292605, -0.138296, 0.028218, 0.533117, 0.545081, -0.013927, 0.000000, 0.000000, 0.000000], [0.335676, -0.175824, 0.243423, -0.325533, -0.319824, -0.027872, 0.766888, 0.000000, 0.000000, 0.000000], [-0.248598, -0.402693, 0.249069, 0.631401, 0.354212, -0.268193, 0.343425, 0.000000, 0.000000, 0.000000], [-0.391878, 0.125746, -0.265087, 0.315429, -0.298042, 0.685746, 0.319025, 0.000000, 0.000000, 0.000000], [0.041926, 0.715712, -0.231981, -0.004516, 0.480950, -0.177328, 0.411588, 0.000000, 0.000000, 0.000000]]
fourier: [[11.997209, 12.282698, 12.679679, 14.629062, 96.040853], [55.815559, 57.359893, 57.794680, 64.703827, 244.062498], [48.554671, 53.984345, 59.586832, 62.459675, 171.953655], [32.224859, 32.749853, 36.741082, 37.961971, 179.693805], [24.639957, 25.714008, 26.908783, 31.852170, 82.068447], [36.812031, 37.130416, 43.049130, 43.745994, 210.443672], [16.142933, 17.438400, 17.603751, 26.528037, 56.521588]]
### 4
mean: [2.422910, -2.084970, 1.010745, -1.698117, 2.815175, 1.317059, 1.508247]
std: [3.669974, 1.824108, 1.645990, 2.073534, 3.853409, 0.833031, 2.103228]
pca: [[0.560100, -0.087292, 0.015124, -0.110166, -0.378230, 0.393377, 0.607041, 0.000000, 0.000000, 0.000000], [-0.273330, 0.049875, 0.847568, -0.089335, 0.255552, 0.031652, 0.360752, 0.000000, 0.000000, 0.000000], [0.250438, 0.100156, 0.087063, 0.627805, 0.409409, 0.559334, -0.212275, 0.000000, 0.000000, 0.000000], [-0.315883, -0.121841, -0.085007, -0.573631, 0.039549, 0.695058, -0.253821, 0.000000, 0.000000, 0.000000], [0.588034, -0.054206, 0.021322, -0.475684, 0.603607, -0.211811, -0.123867, 0.000000, 0.000000, 0.000000], [-0.044823, 0.953236, -0.179068, -0.150294, 0.070352, 0.056300, 0.162968, 0.000000, 0.000000, 0.000000], [0.318252, 0.231125, 0.483811, -0.088480, -0.503154, -0.016104, -0.591584, 0.000000, 0.000000, 0.000000]]
fourier: [[61.004155, 70.827022, 71.797672, 80.558211, 218.061918], [33.073392, 33.237177, 34.781154, 40.230463, 187.647297], [28.153104, 32.609071, 34.342980, 35.074372, 90.967078], [34.999661, 40.198722, 42.277676, 44.911468, 152.830566], [64.254228, 74.995723, 75.543470, 82.896252, 253.365748], [11.905407, 12.218195, 14.977504, 19.311550, 118.535276], [33.964370, 40.248986, 42.810452, 44.809335, 135.742226]]
### 6
mean: [3.732751, -0.648268, -0.610204, 2.599134, -1.648307, -1.090420, -1.308473]
std: [5.581426, 0.947921, 0.344745, 4.233980, 1.221149, 0.667652, 1.321486]
pca: [[0.762307, -0.150009, 0.335968, -0.211740, 0.240898, -0.266189, -0.331343, 0.000000, 0.000000, 0.000000], [-0.127533, -0.385088, 0.394437, 0.434301, -0.341434, 0.333813, -0.513066, 0.000000, 0.000000, 0.000000], [-0.046256, -0.074078, 0.580350, 0.353844, 0.459659, 0.080294, 0.559131, 0.000000, 0.000000, 0.000000], [0.577861, 0.407577, -0.115949, 0.257641, -0.290729, 0.535416, 0.221225, 0.000000, 0.000000, 0.000000], [-0.164264, 0.494733, 0.609016, -0.350115, -0.455001, -0.162021, 0.038718, 0.000000, 0.000000, 0.000000], [-0.084701, 0.599366, -0.049123, 0.538979, 0.280185, -0.316344, -0.402613, 0.000000, 0.000000, 0.000000], [-0.180009, 0.231511, 0.089336, -0.402350, 0.494016, 0.631088, -0.319076, 0.000000, 0.000000, 0.000000]]
fourier: [[91.376612, 105.082174, 110.274278, 121.265162, 335.947579], [16.523976, 16.530338, 18.785554, 20.842078, 58.344131], [5.527150, 5.625366, 6.858514, 7.163036, 54.918349], [70.434706, 77.900199, 83.861068, 92.763767, 233.922066], [22.412499, 23.330249, 23.490524, 25.204005, 148.347599], [12.089480, 12.188549, 13.079582, 13.396868, 98.137794], [22.580349, 24.816328, 25.781055, 28.371937, 117.762544]]
### 8
mean: [-1.304851, -1.657260, -0.985331, 0.096487, 3.850334, -2.286557, 3.880360]
std: [1.552040, 2.093476, 1.463957, 0.665255, 5.182889, 2.562312, 5.099602]
pca: [[-0.187038, 0.592583, -0.236192, 0.046996, 0.533685, 0.458153, -0.247273, 0.000000, 0.000000, 0.000000], [-0.252351, -0.179285, -0.610729, -0.418529, 0.154374, -0.011869, 0.576236, 0.000000, 0.000000, 0.000000], [-0.176436, -0.153540, 0.670374, 0.037946, 0.451209, 0.210635, 0.496485, 0.000000, 0.000000, 0.000000], [-0.080172, -0.251115, 0.069596, -0.295967, -0.433261, 0.797174, -0.121952, 0.000000, 0.000000, 0.000000], [0.624821, 0.543833, 0.132153, -0.356702, -0.170047, 0.054438, 0.370493, 0.000000, 0.000000, 0.000000], [-0.308894, 0.322993, -0.092163, 0.610105, -0.462534, 0.120717, 0.437067, 0.000000, 0.000000, 0.000000], [0.614786, -0.360543, -0.301694, 0.483864, 0.239147, 0.304246, 0.130940, 0.000000, 0.000000, 0.000000]]
fourier: [[26.003003, 28.067463, 30.776484, 33.198200, 117.436571], [35.351165, 38.439270, 41.358493, 44.917249, 149.153377], [24.094385, 26.447884, 28.909705, 31.832154, 88.679771], [10.710806, 11.100954, 12.196413, 13.106605, 14.418706], [86.751433, 94.662629, 102.384324, 111.768353, 346.530086], [42.841557, 46.535498, 50.715729, 55.100914, 205.790114], [85.020126, 92.556035, 100.889648, 109.920998, 349.232377]]
### 10
mean: [0.006979, 2.625640, -1.575768, 3.242582, -0.652764, -2.519723, 0.014078]
std: [1.011417, 3.612183, 1.448498, 4.285143, 0.485772, 2.632771, 0.815996]
pca: [[-0.154973, 0.614195, -0.037045, 0.117603, 0.178969, 0.216603, 0.710351, 0.000000, 0.000000, 0.000000], [0.555037, -0.334306, 0.352102, 0.148020, -0.412823, -0.017611, 0.513377, 0.000000, 0.000000, 0.000000], [-0.222475, -0.348010, -0.303607, 0.800063, 0.006586, 0.311475, 0.007442, 0.000000, 0.000000, 0.000000], [0.658487, -0.004816, -0.326599, 0.111411, 0.650994, -0.153216, -0.004951, 0.000000, 0.000000, 0.000000], [-0.074321, -0.350598, 0.426378, -0.259385, 0.478521, 0.625973, 0.040669, 0.000000, 0.000000, 0.000000], [-0.404460, -0.493499, -0.157911, -0.193900, 0.242356, -0.512196, 0.457445, 0.000000, 0.000000, 0.000000], [-0.125325, 0.153002, 0.684889, 0.454828, 0.293244, -0.422012, -0.144415, 0.000000, 0.000000, 0.000000]]
fourier: [[15.386515, 16.461649, 19.132544, 20.668368, 21.611780], [59.953287, 66.109411, 71.905967, 77.905663, 236.307633], [24.372874, 25.917173, 28.331449, 31.318444, 141.819110], [71.445982, 78.032761, 84.797009, 92.592283, 291.832338], [8.288565, 8.399311, 9.125810, 10.589971, 58.748789], [44.117964, 47.251823, 51.550723, 56.984171, 226.775101], [12.841876, 13.627463, 15.150104, 16.274313, 17.616624]]
### 12
mean: [-2.479802]
std: [3.980276]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[65.647945, 74.184809, 80.010749, 85.449517, 223.182212]]
## 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
The trained model weights:
{
"network.0.weight": [
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0.30837,
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-0.327621,
0.637576
],
[
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0.40406,
0.03318,
0.557385
],
[
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0.207551,
0.516158,
-0.50644
],
[
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-0.081993,
0.281254,
-0.055522,
0.369258
],
[
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0.016385,
0.200766,
0.555014
],
[
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## Activation Signature
### 0
mean: [1.165154, 1.489974, 0.927827, 1.473719, 0.081816, 1.782892, 1.037302]
std: [1.655208, 1.797759, 1.352474, 1.477002, 1.442375, 1.539947, 1.689929]
pca: [[0.476895, -0.103784, -0.168692, -0.333821, 0.596661, -0.078878, -0.509589, 0.000000, 0.000000, 0.000000], [0.475799, 0.197630, -0.051278, 0.670358, -0.281077, -0.342930, -0.293162, 0.000000, 0.000000, 0.000000], [-0.276367, 0.183235, 0.731688, 0.246894, 0.485784, -0.219791, -0.097095, 0.000000, 0.000000, 0.000000], [0.425906, -0.044766, 0.140410, 0.340002, 0.261921, 0.707090, 0.335715, 0.000000, 0.000000, 0.000000], [0.000511, 0.729004, -0.395061, -0.020875, 0.330247, -0.183382, 0.411523, 0.000000, 0.000000, 0.000000], [0.262818, 0.560890, 0.411381, -0.443676, -0.384672, 0.247501, -0.202524, 0.000000, 0.000000, 0.000000], [0.468335, -0.261814, 0.297529, -0.255620, -0.058029, -0.482708, 0.567342, 0.000000, 0.000000, 0.000000]]
fourier: [[26.698355, 29.700380, 31.232834, 32.875564, 104.863816], [30.492579, 31.663515, 37.992999, 38.204933, 134.097651], [19.241855, 21.993657, 22.518877, 23.722246, 83.504450], [25.603760, 26.712906, 29.803081, 32.617929, 132.634694], [20.116044, 20.550117, 21.095018, 21.279287, 24.941410], [24.222441, 26.103092, 27.394443, 29.761115, 160.460305], [26.435399, 28.456994, 31.125244, 34.088202, 93.357221]]
### 2
mean: [1.067121, 2.711805, 1.910596, 1.996598, -0.911872, -2.338263, 0.628018]
std: [0.779283, 3.074395, 2.880107, 1.740880, 1.436347, 2.014948, 1.090673]
pca: [[-0.017359, 0.362971, 0.856842, 0.036474, 0.095045, 0.332298, -0.113962, 0.000000, 0.000000, 0.000000], [0.597456, 0.247998, -0.036339, 0.627469, -0.398569, -0.134417, -0.097874, 0.000000, 0.000000, 0.000000], [0.559410, -0.292605, -0.138296, 0.028218, 0.533117, 0.545081, -0.013927, 0.000000, 0.000000, 0.000000], [0.335676, -0.175824, 0.243423, -0.325533, -0.319824, -0.027872, 0.766888, 0.000000, 0.000000, 0.000000], [-0.248598, -0.402693, 0.249069, 0.631401, 0.354212, -0.268193, 0.343425, 0.000000, 0.000000, 0.000000], [-0.391878, 0.125746, -0.265087, 0.315429, -0.298042, 0.685746, 0.319025, 0.000000, 0.000000, 0.000000], [0.041926, 0.715712, -0.231981, -0.004516, 0.480950, -0.177328, 0.411588, 0.000000, 0.000000, 0.000000]]
fourier: [[11.997209, 12.282698, 12.679679, 14.629062, 96.040853], [55.815559, 57.359893, 57.794680, 64.703827, 244.062498], [48.554671, 53.984345, 59.586832, 62.459675, 171.953655], [32.224859, 32.749853, 36.741082, 37.961971, 179.693805], [24.639957, 25.714008, 26.908783, 31.852170, 82.068447], [36.812031, 37.130416, 43.049130, 43.745994, 210.443672], [16.142933, 17.438400, 17.603751, 26.528037, 56.521588]]
### 4
mean: [2.422910, -2.084970, 1.010745, -1.698117, 2.815175, 1.317059, 1.508247]
std: [3.669974, 1.824108, 1.645990, 2.073534, 3.853409, 0.833031, 2.103228]
pca: [[0.560100, -0.087292, 0.015124, -0.110166, -0.378230, 0.393377, 0.607041, 0.000000, 0.000000, 0.000000], [-0.273330, 0.049875, 0.847568, -0.089335, 0.255552, 0.031652, 0.360752, 0.000000, 0.000000, 0.000000], [0.250438, 0.100156, 0.087063, 0.627805, 0.409409, 0.559334, -0.212275, 0.000000, 0.000000, 0.000000], [-0.315883, -0.121841, -0.085007, -0.573631, 0.039549, 0.695058, -0.253821, 0.000000, 0.000000, 0.000000], [0.588034, -0.054206, 0.021322, -0.475684, 0.603607, -0.211811, -0.123867, 0.000000, 0.000000, 0.000000], [-0.044823, 0.953236, -0.179068, -0.150294, 0.070352, 0.056300, 0.162968, 0.000000, 0.000000, 0.000000], [0.318252, 0.231125, 0.483811, -0.088480, -0.503154, -0.016104, -0.591584, 0.000000, 0.000000, 0.000000]]
fourier: [[61.004155, 70.827022, 71.797672, 80.558211, 218.061918], [33.073392, 33.237177, 34.781154, 40.230463, 187.647297], [28.153104, 32.609071, 34.342980, 35.074372, 90.967078], [34.999661, 40.198722, 42.277676, 44.911468, 152.830566], [64.254228, 74.995723, 75.543470, 82.896252, 253.365748], [11.905407, 12.218195, 14.977504, 19.311550, 118.535276], [33.964370, 40.248986, 42.810452, 44.809335, 135.742226]]
### 6
mean: [3.732751, -0.648268, -0.610204, 2.599134, -1.648307, -1.090420, -1.308473]
std: [5.581426, 0.947921, 0.344745, 4.233980, 1.221149, 0.667652, 1.321486]
pca: [[0.762307, -0.150009, 0.335968, -0.211740, 0.240898, -0.266189, -0.331343, 0.000000, 0.000000, 0.000000], [-0.127533, -0.385088, 0.394437, 0.434301, -0.341434, 0.333813, -0.513066, 0.000000, 0.000000, 0.000000], [-0.046256, -0.074078, 0.580350, 0.353844, 0.459659, 0.080294, 0.559131, 0.000000, 0.000000, 0.000000], [0.577861, 0.407577, -0.115949, 0.257641, -0.290729, 0.535416, 0.221225, 0.000000, 0.000000, 0.000000], [-0.164264, 0.494733, 0.609016, -0.350115, -0.455001, -0.162021, 0.038718, 0.000000, 0.000000, 0.000000], [-0.084701, 0.599366, -0.049123, 0.538979, 0.280185, -0.316344, -0.402613, 0.000000, 0.000000, 0.000000], [-0.180009, 0.231511, 0.089336, -0.402350, 0.494016, 0.631088, -0.319076, 0.000000, 0.000000, 0.000000]]
fourier: [[91.376612, 105.082174, 110.274278, 121.265162, 335.947579], [16.523976, 16.530338, 18.785554, 20.842078, 58.344131], [5.527150, 5.625366, 6.858514, 7.163036, 54.918349], [70.434706, 77.900199, 83.861068, 92.763767, 233.922066], [22.412499, 23.330249, 23.490524, 25.204005, 148.347599], [12.089480, 12.188549, 13.079582, 13.396868, 98.137794], [22.580349, 24.816328, 25.781055, 28.371937, 117.762544]]
### 8
mean: [-1.304851, -1.657260, -0.985331, 0.096487, 3.850334, -2.286557, 3.880360]
std: [1.552040, 2.093476, 1.463957, 0.665255, 5.182889, 2.562312, 5.099602]
pca: [[-0.187038, 0.592583, -0.236192, 0.046996, 0.533685, 0.458153, -0.247273, 0.000000, 0.000000, 0.000000], [-0.252351, -0.179285, -0.610729, -0.418529, 0.154374, -0.011869, 0.576236, 0.000000, 0.000000, 0.000000], [-0.176436, -0.153540, 0.670374, 0.037946, 0.451209, 0.210635, 0.496485, 0.000000, 0.000000, 0.000000], [-0.080172, -0.251115, 0.069596, -0.295967, -0.433261, 0.797174, -0.121952, 0.000000, 0.000000, 0.000000], [0.624821, 0.543833, 0.132153, -0.356702, -0.170047, 0.054438, 0.370493, 0.000000, 0.000000, 0.000000], [-0.308894, 0.322993, -0.092163, 0.610105, -0.462534, 0.120717, 0.437067, 0.000000, 0.000000, 0.000000], [0.614786, -0.360543, -0.301694, 0.483864, 0.239147, 0.304246, 0.130940, 0.000000, 0.000000, 0.000000]]
fourier: [[26.003003, 28.067463, 30.776484, 33.198200, 117.436571], [35.351165, 38.439270, 41.358493, 44.917249, 149.153377], [24.094385, 26.447884, 28.909705, 31.832154, 88.679771], [10.710806, 11.100954, 12.196413, 13.106605, 14.418706], [86.751433, 94.662629, 102.384324, 111.768353, 346.530086], [42.841557, 46.535498, 50.715729, 55.100914, 205.790114], [85.020126, 92.556035, 100.889648, 109.920998, 349.232377]]
### 10
mean: [0.006979, 2.625640, -1.575768, 3.242582, -0.652764, -2.519723, 0.014078]
std: [1.011417, 3.612183, 1.448498, 4.285143, 0.485772, 2.632771, 0.815996]
pca: [[-0.154973, 0.614195, -0.037045, 0.117603, 0.178969, 0.216603, 0.710351, 0.000000, 0.000000, 0.000000], [0.555037, -0.334306, 0.352102, 0.148020, -0.412823, -0.017611, 0.513377, 0.000000, 0.000000, 0.000000], [-0.222475, -0.348010, -0.303607, 0.800063, 0.006586, 0.311475, 0.007442, 0.000000, 0.000000, 0.000000], [0.658487, -0.004816, -0.326599, 0.111411, 0.650994, -0.153216, -0.004951, 0.000000, 0.000000, 0.000000], [-0.074321, -0.350598, 0.426378, -0.259385, 0.478521, 0.625973, 0.040669, 0.000000, 0.000000, 0.000000], [-0.404460, -0.493499, -0.157911, -0.193900, 0.242356, -0.512196, 0.457445, 0.000000, 0.000000, 0.000000], [-0.125325, 0.153002, 0.684889, 0.454828, 0.293244, -0.422012, -0.144415, 0.000000, 0.000000, 0.000000]]
fourier: [[15.386515, 16.461649, 19.132544, 20.668368, 21.611780], [59.953287, 66.109411, 71.905967, 77.905663, 236.307633], [24.372874, 25.917173, 28.331449, 31.318444, 141.819110], [71.445982, 78.032761, 84.797009, 92.592283, 291.832338], [8.288565, 8.399311, 9.125810, 10.589971, 58.748789], [44.117964, 47.251823, 51.550723, 56.984171, 226.775101], [12.841876, 13.627463, 15.150104, 16.274313, 17.616624]]
### 12
mean: [-2.479802]
std: [3.980276]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[65.647945, 74.184809, 80.010749, 85.449517, 223.182212]]
## 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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{"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": [[0.363811, 0.30837, -0.057852, -0.327621, 0.637576], [0.398949, -0.371709, 0.40406, 0.03318, 0.557385], [-0.166027, -0.10407, 0.207551, 0.516158, -0.50644], [0.446042, -0.081993, 0.281254, -0.055522, 0.369258], [-0.465314, -0.138336, 0.016385, 0.200766, 0.555014], [0.097662, 0.144082, -0.126004, 0.392236, 0.593542], [0.612951, 0.267391, -0.030943, -0.161546, 0.364812]], "network.0.bias": [0.18756, 0.068211, 0.408264, 0.144192, -0.236323, 0.088852, -0.251598], "network.2.weight": [[0.117747, 0.033111, 0.572702, 0.431288, -0.621179, 0.098447, -0.285633], [0.597502, 0.35115, -0.249636, 0.28857, 0.095608, 0.08674, 0.716953], [0.646757, 0.014054, -0.558019, 0.257887, 0.483559, 0.45041, 0.419494], [0.319699, 0.078293, -0.112349, 0.163355, 0.439589, 0.257439, 0.31435], [-0.144528, -0.657671, 0.062263, -0.181881, -0.085183, 0.265287, -0.041105], [-0.256867, -0.128988, 0.236629, -0.287468, -0.286744, -0.38846, -0.302721], [-0.074913, 0.489333, 0.052476, 0.438431, -0.640302, -0.33108, -0.278395]], "network.2.bias": [0.073542, 0.146754, -0.307473, 0.257323, 0.152803, -0.410207, 0.494632], "network.4.weight": [[-0.481392, 0.406732, 0.742273, 0.283218, 0.00927, -0.294848, -0.333664], [-0.197478, -0.049061, -0.389899, -0.421041, -0.220689, 0.169451, 0.359175], [-0.224632, 0.15841, 0.096546, 0.497085, -0.31083, -0.276197, 0.010193], [0.256569, -0.145033, -0.366096, -0.353945, 0.133827, 0.26132, -0.047853], [-0.364065, 0.531781, 0.743954, 0.173912, -0.503415, -0.158222, -0.522323], [0.537094, 0.083264, -0.214697, 0.029792, 0.333195, -0.185538, 0.555337], [-0.419687, 0.304387, 0.431431, -0.020816, 0.126213, -0.353438, 0.155895]], "network.4.bias": [-0.055359, -0.312834, -0.342214, -0.071117, 0.29899, 0.420534, 0.113145], "network.6.weight": [[0.433798, 0.101159, 0.343026, -0.210661, 0.741087, -0.407816, 0.371085], [-0.183726, -0.205893, -0.269014, 0.104913, -0.096606, 0.233798, 0.265597], [-0.300692, -0.012717, 0.19471, 0.054434, -0.01625, -0.008649, 0.233479], [0.425925, 0.403458, 0.307976, 0.197776, 0.526956, -0.56818, 0.110569], [-0.293196, 0.286321, 0.188573, -0.31646, -0.182767, -0.214505, 0.06327], [-0.079117, 0.063085, 0.333313, 0.281314, -0.183448, -0.29305, -0.123676], [-0.320039, 0.055494, 0.230204, -0.11181, -0.069405, -0.017692, -0.162071]], "network.6.bias": [-0.118064, -0.295796, -0.348552, 0.077765, -0.332249, -0.134236, -0.212899], "network.8.weight": [[-0.086057, -0.335684, 0.125762, -0.283474, -0.271263, 0.333773, 0.095246], [-0.369533, -0.270157, 0.175573, -0.038045, 0.347483, -0.242982, 0.335416], [-0.12791, 0.268845, 0.072063, -0.197577, 0.257447, -0.170965, -0.103322], [-0.127652, 0.082111, -0.310366, 0.003682, 0.043245, -0.226822, 0.285232], [0.764636, 0.073325, -0.103626, 0.290439, 0.21981, 0.260222, 0.264146], [-0.250237, -0.229891, 0.194832, -0.318405, -0.241555, -0.086093, 0.182887], [0.500615, 0.17182, 0.368907, 0.626968, 0.329017, 0.36976, -0.148254]], "network.8.bias": [-0.086177, -0.01586, 0.11234, 0.602893, -0.149874, -0.298081, -0.050796], "network.10.weight": [[-0.059202, 0.223875, 0.005126, 0.573704, 0.048476, -0.376752, -0.219132], [0.077019, 0.254824, -0.165334, -0.41936, 0.121238, 0.329741, 0.565482], [-0.296024, -0.241607, -0.290271, -0.130355, -0.195542, 0.102516, -0.096706], [0.336736, -0.365908, -0.364731, -0.159286, 0.50896, -0.284448, 0.317276], [-0.096633, -0.148881, 0.232126, -0.31614, -0.252751, 0.027758, 0.146931], [0.031207, 0.024087, 0.174964, -0.327612, -0.286967, 0.259192, -0.24198], [0.026118, -0.029331, 0.056746, 0.203173, -0.336845, 0.110608, 0.189965]], "network.10.bias": [0.474429, 0.102724, -0.368625, 0.093123, -0.143395, -0.353475, 0.51989], "network.12.weight": [[0.469468, -0.388394, -0.174659, -0.54624, 0.000808, 0.006974, 0.437325]], "network.12.bias": [-0.008085]}}
|
{"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.678806722164154, "train_acc": 0.58, "val_loss": 0.7120968699455261, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.678398996591568, "train_acc": 0.58, "val_loss": 0.7120597958564758, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6796444654464722, "train_acc": 0.58, "val_loss": 0.6994892954826355, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6600531339645386, "train_acc": 0.58, "val_loss": 0.6619260311126709, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.647042989730835, "train_acc": 0.505, "val_loss": 0.5627245903015137, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5618963539600372, "train_acc": 0.575, "val_loss": 0.44926032423973083, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4635019898414612, "train_acc": 0.83, "val_loss": 0.3618110716342926, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.408489853143692, "train_acc": 0.84, "val_loss": 0.31284525990486145, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.3704707622528076, "train_acc": 0.84, "val_loss": 0.27542248368263245, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.36919014155864716, "train_acc": 0.845, "val_loss": 0.2531663775444031, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3340695947408676, "train_acc": 0.855, "val_loss": 0.38814613223075867, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.35171355307102203, "train_acc": 0.855, "val_loss": 0.2710587680339813, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.36843225359916687, "train_acc": 0.855, "val_loss": 0.20432095229625702, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.33419349789619446, "train_acc": 0.855, "val_loss": 0.21394413709640503, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7120968699455261, "final_val_loss": 0.6619260311126709, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5627245903015137, "final_val_loss": 0.21394413709640503, "initial_val_acc": 0.48, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.45999999999999996, "first_improvement_epoch": 3}}
|
2
|
{"target_pattern": "alternating", "degraded_accuracy": 0.52, "improved_accuracy": 0.82, "improvement": 0.29999999999999993, "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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],
[
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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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0.711041,
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],
[
0.316988,
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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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[
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"network.6.weight": [
[
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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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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [2.086291, -2.114761, -1.033208, 0.079286, 2.422832, -0.417565, -1.790624]
std: [1.600304, 2.039458, 1.141797, 1.991950, 1.626940, 1.040294, 2.243515]
pca: [[-0.335274, -0.129240, 0.633967, 0.058881, -0.190209, 0.388992, -0.527269, 0.000000, 0.000000, 0.000000], [0.124285, 0.792916, 0.381325, 0.110486, 0.404305, -0.170909, -0.074493, 0.000000, 0.000000, 0.000000], [-0.140846, 0.231235, 0.190180, -0.652576, -0.144625, 0.397805, 0.534325, 0.000000, 0.000000, 0.000000], [-0.444360, 0.354046, -0.620542, 0.049245, 0.148513, 0.438035, -0.275257, 0.000000, 0.000000, 0.000000], [-0.413779, -0.335401, 0.170177, 0.261630, 0.667005, 0.092455, 0.406742, 0.000000, 0.000000, 0.000000], [0.047404, 0.205624, 0.044466, 0.698095, -0.451187, 0.286396, 0.424930, 0.000000, 0.000000, 0.000000], [0.693823, -0.144871, -0.022326, 0.016061, 0.330030, 0.615452, -0.095729, 0.000000, 0.000000, 0.000000]]
fourier: [[24.404501, 26.297405, 27.819125, 28.097119, 187.766172], [32.877138, 33.291828, 35.612435, 38.124288, 190.328536], [18.127157, 18.618158, 20.345100, 22.458540, 92.988741], [31.217009, 35.659065, 37.301275, 40.340365, 40.424718], [25.599336, 26.087852, 29.070942, 29.238285, 218.054828], [15.719936, 16.183363, 19.464417, 20.681868, 37.580860], [31.805223, 35.624600, 35.724460, 37.069936, 161.156157]]
### 2
mean: [0.464410, 0.877251, -0.271403, 0.746385, 0.598007, 1.534507, -0.028191]
std: [0.734039, 0.858417, 0.476855, 1.120179, 0.705911, 1.161759, 0.605105]
pca: [[-0.197931, 0.499335, 0.698166, -0.135236, 0.119888, 0.433232, 0.060833, 0.000000, 0.000000, 0.000000], [0.435907, 0.159445, -0.081565, 0.621598, 0.297754, 0.321211, -0.446868, 0.000000, 0.000000, 0.000000], [-0.015625, -0.403873, -0.297421, -0.341039, 0.246035, 0.746152, 0.120826, 0.000000, 0.000000, 0.000000], [0.585500, -0.107304, 0.258410, -0.601625, 0.082417, -0.176459, -0.423105, 0.000000, 0.000000, 0.000000], [-0.100481, 0.581593, -0.505866, -0.284150, -0.409740, 0.171820, -0.342933, 0.000000, 0.000000, 0.000000], [0.586875, 0.371556, -0.173541, -0.049672, 0.047912, -0.006767, 0.694694, 0.000000, 0.000000, 0.000000], [-0.270621, 0.272600, -0.254282, -0.184007, 0.812072, -0.302795, -0.052816, 0.000000, 0.000000, 0.000000]]
fourier: [[11.193247, 11.612430, 12.478527, 13.261890, 41.796875], [12.434334, 13.903177, 14.776922, 17.286949, 78.952601], [6.755429, 7.091038, 8.054942, 8.757544, 24.426282], [16.162466, 17.087799, 18.528281, 20.784576, 67.174607], [10.554293, 11.367883, 13.236867, 15.027589, 53.820673], [18.266538, 18.830069, 19.043608, 22.791912, 138.105619], [8.644760, 8.765242, 8.886149, 8.947545, 10.679740]]
### 4
mean: [0.123427, 0.722329, 1.291103, -0.652337, 0.032877, -0.249137, -1.228097]
std: [0.866571, 1.119639, 1.272631, 0.479970, 0.365991, 0.285343, 0.947706]
pca: [[0.385924, 0.355229, 0.469050, -0.433192, -0.242174, -0.150256, 0.485784, 0.000000, 0.000000, 0.000000], [0.513320, -0.363406, 0.465980, 0.065235, -0.139935, 0.338513, -0.498871, 0.000000, 0.000000, 0.000000], [0.594645, -0.259329, -0.197105, 0.274809, 0.540747, -0.213268, 0.356209, 0.000000, 0.000000, 0.000000], [-0.193688, -0.438331, 0.161995, 0.477196, -0.495459, 0.064518, 0.516479, 0.000000, 0.000000, 0.000000], [0.125539, 0.414838, 0.134857, 0.574425, -0.208774, -0.573491, -0.302522, 0.000000, 0.000000, 0.000000], [-0.038222, 0.518203, 0.197373, 0.417910, 0.286795, 0.635746, 0.173135, 0.000000, 0.000000, 0.000000], [-0.423350, -0.204298, 0.663792, -0.015511, 0.507981, -0.283056, -0.003351, 0.000000, 0.000000, 0.000000]]
fourier: [[12.025815, 12.641251, 13.737659, 15.414318, 16.115832], [16.840328, 17.421670, 18.956892, 19.167009, 65.009598], [19.067750, 20.489536, 21.431384, 24.388282, 116.199291], [7.281061, 8.233337, 8.837537, 9.845798, 58.710313], [5.292872, 5.596353, 5.898684, 6.248987, 6.349248], [4.254926, 4.650854, 5.097003, 5.750386, 22.422324], [14.695571, 15.190015, 15.727100, 19.216978, 110.528747]]
### 6
mean: [0.177022, 0.143676, 0.115426, 0.288151, 0.142274, -0.363924, 1.059961]
std: [0.146340, 0.384036, 0.133834, 0.466325, 0.170299, 0.351265, 0.984926]
pca: [[-0.097581, 0.396333, -0.348603, 0.043662, 0.790988, -0.075305, -0.280419, 0.000000, 0.000000, 0.000000], [0.314365, -0.174937, 0.096215, 0.277408, 0.200223, 0.857075, -0.098447, 0.000000, 0.000000, 0.000000], [-0.104234, -0.206446, 0.107387, 0.129209, 0.428276, -0.059604, 0.855170, 0.000000, 0.000000, 0.000000], [0.378780, -0.116511, -0.528094, 0.674928, -0.173401, -0.275629, 0.050010, 0.000000, 0.000000, 0.000000], [-0.091454, 0.644982, -0.399052, -0.112617, -0.326811, 0.368853, 0.401062, 0.000000, 0.000000, 0.000000], [-0.273998, 0.451121, 0.559588, 0.628927, -0.074159, -0.063033, -0.057041, 0.000000, 0.000000, 0.000000], [0.808625, 0.369608, 0.326224, -0.201704, 0.091954, -0.200502, 0.117272, 0.000000, 0.000000, 0.000000]]
fourier: [[2.242841, 2.453253, 2.637503, 2.867315, 15.931947], [6.123289, 6.257718, 6.330092, 7.877686, 12.930809], [1.954446, 1.969912, 2.114788, 2.406848, 10.388320], [7.336666, 7.349611, 8.582070, 8.726519, 25.933596], [2.760325, 2.762842, 2.912243, 3.178820, 12.804621], [5.677163, 6.013511, 6.387714, 6.459640, 32.753122], [14.236476, 15.101911, 16.504978, 20.121234, 95.396474]]
### 8
mean: [0.228473, 0.585342, -0.118214, 0.619765, -0.086756, 0.157927, 0.062501]
std: [0.076876, 0.362631, 0.298687, 0.911769, 0.378602, 0.148888, 0.152884]
pca: [[0.064019, -0.145943, -0.527797, 0.163834, 0.228827, 0.690997, 0.373298, 0.000000, 0.000000, 0.000000], [0.324453, 0.295719, 0.500239, 0.278419, -0.093339, 0.578621, -0.368794, 0.000000, 0.000000, 0.000000], [-0.263308, 0.760270, 0.184046, -0.054544, 0.153982, -0.004478, 0.540444, 0.000000, 0.000000, 0.000000], [0.819288, 0.130772, -0.128570, 0.282346, 0.016473, -0.370001, 0.279721, 0.000000, 0.000000, 0.000000], [-0.339801, 0.091393, -0.211696, 0.732089, -0.532345, -0.109619, 0.002623, 0.000000, 0.000000, 0.000000], [-0.132498, 0.205355, -0.214082, 0.353285, 0.727157, -0.187383, -0.453610, 0.000000, 0.000000, 0.000000], [-0.130563, -0.495596, 0.574579, 0.390106, 0.320618, -0.060584, 0.385419, 0.000000, 0.000000, 0.000000]]
fourier: [[1.159686, 1.307035, 1.409086, 1.414942, 20.562592], [5.461898, 5.821539, 6.163703, 7.506495, 52.680815], [4.622323, 5.085646, 5.117264, 6.079859, 10.639248], [14.144360, 15.094719, 15.171667, 18.756267, 55.778821], [5.890417, 6.033591, 6.475655, 7.808007, 7.939959], [2.305506, 2.377218, 2.509061, 3.158192, 14.213438], [2.307971, 2.348916, 2.405106, 2.910492, 5.625095]]
### 10
mean: [-0.113212]
std: [0.530438]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[8.407553, 8.746714, 8.806268, 10.189054, 11.156936]]
## 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:
{
"network.0.weight": [
[
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],
[
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[
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],
[
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],
[
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],
[
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],
[
0.440509,
-0.408169,
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-0.204967
]
],
"network.0.bias": [
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-0.429665,
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0.148447,
-0.242481,
-0.463063
],
"network.2.weight": [
[
-0.151067,
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],
[
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0.020468,
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0.028018,
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],
[
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-0.244134,
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],
[
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0.711041,
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],
[
0.316988,
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0.081923,
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],
[
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0.509284,
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0.203331,
0.23205,
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],
[
0.046501,
0.205985,
0.052768,
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-0.249155,
-0.029869,
0.318524
]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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[
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[
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[
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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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[
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],
[
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]
],
"network.6.bias": [
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"network.8.weight": [
[
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],
[
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],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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]
],
"network.10.bias": [
0.265813
]
}
## Activation Signature
### 0
mean: [2.086291, -2.114761, -1.033208, 0.079286, 2.422832, -0.417565, -1.790624]
std: [1.600304, 2.039458, 1.141797, 1.991950, 1.626940, 1.040294, 2.243515]
pca: [[-0.335274, -0.129240, 0.633967, 0.058881, -0.190209, 0.388992, -0.527269, 0.000000, 0.000000, 0.000000], [0.124285, 0.792916, 0.381325, 0.110486, 0.404305, -0.170909, -0.074493, 0.000000, 0.000000, 0.000000], [-0.140846, 0.231235, 0.190180, -0.652576, -0.144625, 0.397805, 0.534325, 0.000000, 0.000000, 0.000000], [-0.444360, 0.354046, -0.620542, 0.049245, 0.148513, 0.438035, -0.275257, 0.000000, 0.000000, 0.000000], [-0.413779, -0.335401, 0.170177, 0.261630, 0.667005, 0.092455, 0.406742, 0.000000, 0.000000, 0.000000], [0.047404, 0.205624, 0.044466, 0.698095, -0.451187, 0.286396, 0.424930, 0.000000, 0.000000, 0.000000], [0.693823, -0.144871, -0.022326, 0.016061, 0.330030, 0.615452, -0.095729, 0.000000, 0.000000, 0.000000]]
fourier: [[24.404501, 26.297405, 27.819125, 28.097119, 187.766172], [32.877138, 33.291828, 35.612435, 38.124288, 190.328536], [18.127157, 18.618158, 20.345100, 22.458540, 92.988741], [31.217009, 35.659065, 37.301275, 40.340365, 40.424718], [25.599336, 26.087852, 29.070942, 29.238285, 218.054828], [15.719936, 16.183363, 19.464417, 20.681868, 37.580860], [31.805223, 35.624600, 35.724460, 37.069936, 161.156157]]
### 2
mean: [0.464410, 0.877251, -0.271403, 0.746385, 0.598007, 1.534507, -0.028191]
std: [0.734039, 0.858417, 0.476855, 1.120179, 0.705911, 1.161759, 0.605105]
pca: [[-0.197931, 0.499335, 0.698166, -0.135236, 0.119888, 0.433232, 0.060833, 0.000000, 0.000000, 0.000000], [0.435907, 0.159445, -0.081565, 0.621598, 0.297754, 0.321211, -0.446868, 0.000000, 0.000000, 0.000000], [-0.015625, -0.403873, -0.297421, -0.341039, 0.246035, 0.746152, 0.120826, 0.000000, 0.000000, 0.000000], [0.585500, -0.107304, 0.258410, -0.601625, 0.082417, -0.176459, -0.423105, 0.000000, 0.000000, 0.000000], [-0.100481, 0.581593, -0.505866, -0.284150, -0.409740, 0.171820, -0.342933, 0.000000, 0.000000, 0.000000], [0.586875, 0.371556, -0.173541, -0.049672, 0.047912, -0.006767, 0.694694, 0.000000, 0.000000, 0.000000], [-0.270621, 0.272600, -0.254282, -0.184007, 0.812072, -0.302795, -0.052816, 0.000000, 0.000000, 0.000000]]
fourier: [[11.193247, 11.612430, 12.478527, 13.261890, 41.796875], [12.434334, 13.903177, 14.776922, 17.286949, 78.952601], [6.755429, 7.091038, 8.054942, 8.757544, 24.426282], [16.162466, 17.087799, 18.528281, 20.784576, 67.174607], [10.554293, 11.367883, 13.236867, 15.027589, 53.820673], [18.266538, 18.830069, 19.043608, 22.791912, 138.105619], [8.644760, 8.765242, 8.886149, 8.947545, 10.679740]]
### 4
mean: [0.123427, 0.722329, 1.291103, -0.652337, 0.032877, -0.249137, -1.228097]
std: [0.866571, 1.119639, 1.272631, 0.479970, 0.365991, 0.285343, 0.947706]
pca: [[0.385924, 0.355229, 0.469050, -0.433192, -0.242174, -0.150256, 0.485784, 0.000000, 0.000000, 0.000000], [0.513320, -0.363406, 0.465980, 0.065235, -0.139935, 0.338513, -0.498871, 0.000000, 0.000000, 0.000000], [0.594645, -0.259329, -0.197105, 0.274809, 0.540747, -0.213268, 0.356209, 0.000000, 0.000000, 0.000000], [-0.193688, -0.438331, 0.161995, 0.477196, -0.495459, 0.064518, 0.516479, 0.000000, 0.000000, 0.000000], [0.125539, 0.414838, 0.134857, 0.574425, -0.208774, -0.573491, -0.302522, 0.000000, 0.000000, 0.000000], [-0.038222, 0.518203, 0.197373, 0.417910, 0.286795, 0.635746, 0.173135, 0.000000, 0.000000, 0.000000], [-0.423350, -0.204298, 0.663792, -0.015511, 0.507981, -0.283056, -0.003351, 0.000000, 0.000000, 0.000000]]
fourier: [[12.025815, 12.641251, 13.737659, 15.414318, 16.115832], [16.840328, 17.421670, 18.956892, 19.167009, 65.009598], [19.067750, 20.489536, 21.431384, 24.388282, 116.199291], [7.281061, 8.233337, 8.837537, 9.845798, 58.710313], [5.292872, 5.596353, 5.898684, 6.248987, 6.349248], [4.254926, 4.650854, 5.097003, 5.750386, 22.422324], [14.695571, 15.190015, 15.727100, 19.216978, 110.528747]]
### 6
mean: [0.177022, 0.143676, 0.115426, 0.288151, 0.142274, -0.363924, 1.059961]
std: [0.146340, 0.384036, 0.133834, 0.466325, 0.170299, 0.351265, 0.984926]
pca: [[-0.097581, 0.396333, -0.348603, 0.043662, 0.790988, -0.075305, -0.280419, 0.000000, 0.000000, 0.000000], [0.314365, -0.174937, 0.096215, 0.277408, 0.200223, 0.857075, -0.098447, 0.000000, 0.000000, 0.000000], [-0.104234, -0.206446, 0.107387, 0.129209, 0.428276, -0.059604, 0.855170, 0.000000, 0.000000, 0.000000], [0.378780, -0.116511, -0.528094, 0.674928, -0.173401, -0.275629, 0.050010, 0.000000, 0.000000, 0.000000], [-0.091454, 0.644982, -0.399052, -0.112617, -0.326811, 0.368853, 0.401062, 0.000000, 0.000000, 0.000000], [-0.273998, 0.451121, 0.559588, 0.628927, -0.074159, -0.063033, -0.057041, 0.000000, 0.000000, 0.000000], [0.808625, 0.369608, 0.326224, -0.201704, 0.091954, -0.200502, 0.117272, 0.000000, 0.000000, 0.000000]]
fourier: [[2.242841, 2.453253, 2.637503, 2.867315, 15.931947], [6.123289, 6.257718, 6.330092, 7.877686, 12.930809], [1.954446, 1.969912, 2.114788, 2.406848, 10.388320], [7.336666, 7.349611, 8.582070, 8.726519, 25.933596], [2.760325, 2.762842, 2.912243, 3.178820, 12.804621], [5.677163, 6.013511, 6.387714, 6.459640, 32.753122], [14.236476, 15.101911, 16.504978, 20.121234, 95.396474]]
### 8
mean: [0.228473, 0.585342, -0.118214, 0.619765, -0.086756, 0.157927, 0.062501]
std: [0.076876, 0.362631, 0.298687, 0.911769, 0.378602, 0.148888, 0.152884]
pca: [[0.064019, -0.145943, -0.527797, 0.163834, 0.228827, 0.690997, 0.373298, 0.000000, 0.000000, 0.000000], [0.324453, 0.295719, 0.500239, 0.278419, -0.093339, 0.578621, -0.368794, 0.000000, 0.000000, 0.000000], [-0.263308, 0.760270, 0.184046, -0.054544, 0.153982, -0.004478, 0.540444, 0.000000, 0.000000, 0.000000], [0.819288, 0.130772, -0.128570, 0.282346, 0.016473, -0.370001, 0.279721, 0.000000, 0.000000, 0.000000], [-0.339801, 0.091393, -0.211696, 0.732089, -0.532345, -0.109619, 0.002623, 0.000000, 0.000000, 0.000000], [-0.132498, 0.205355, -0.214082, 0.353285, 0.727157, -0.187383, -0.453610, 0.000000, 0.000000, 0.000000], [-0.130563, -0.495596, 0.574579, 0.390106, 0.320618, -0.060584, 0.385419, 0.000000, 0.000000, 0.000000]]
fourier: [[1.159686, 1.307035, 1.409086, 1.414942, 20.562592], [5.461898, 5.821539, 6.163703, 7.506495, 52.680815], [4.622323, 5.085646, 5.117264, 6.079859, 10.639248], [14.144360, 15.094719, 15.171667, 18.756267, 55.778821], [5.890417, 6.033591, 6.475655, 7.808007, 7.939959], [2.305506, 2.377218, 2.509061, 3.158192, 14.213438], [2.307971, 2.348916, 2.405106, 2.910492, 5.625095]]
### 10
mean: [-0.113212]
std: [0.530438]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[8.407553, 8.746714, 8.806268, 10.189054, 11.156936]]
## 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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11.156935773383847]}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "pca", "fourier"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "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": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.364313, 0.06905, 0.257017, 0.404946, 0.532447], [-0.791896, -0.352425, 0.02946, -0.254673, -0.06563], [-0.194295, -0.07244, -0.403854, 0.050091, 0.410624], [-0.237965, 0.45356, -0.616134, 0.402516, -0.36863], [-0.174858, 0.531054, 0.163938, 0.391273, 0.277926], [-0.234097, -0.191487, 0.35586, 0.110772, -0.418158], [0.440509, -0.408169, 0.355067, -0.75585, -0.204967]], "network.0.bias": [0.351885, 0.078442, -0.429665, 0.427438, 0.148447, -0.242481, -0.463063], "network.2.weight": [[-0.151067, 0.599727, -0.224348, 0.531742, 0.187529, 0.017043, 0.207555], [0.425064, -0.398401, 0.020468, -0.35664, 0.053098, 0.028018, -0.601091], [-0.106733, 0.393223, 0.161742, -0.244134, -0.088523, 0.195466, 0.067212], [-0.015966, -0.049537, 0.711041, -0.749366, 0.490751, 0.654144, -0.267517], [0.316988, -0.409473, 0.081923, 0.539757, -0.206256, -0.240451, 0.549102], [0.463093, -0.207145, 0.509284, -0.38074, 0.203331, 0.23205, -0.297225], [0.046501, 0.205985, 0.052768, 0.551907, -0.249155, -0.029869, 0.318524]], "network.2.bias": [-0.016599, 0.175131, 0.303298, 0.047026, 0.002198, 0.341676, 0.06984], "network.4.weight": [[-0.420074, 0.299282, -0.190138, -0.261044, -0.245347, 0.485517, -0.30116], [-0.256192, 0.048596, -0.003212, 0.563823, -0.293845, 0.258817, -0.412], [-0.129497, 0.313938, 0.060679, 0.653334, -0.166111, 0.29251, -0.086539], [0.041093, -0.509528, -0.165223, 0.463375, 0.192947, -0.359645, -0.073543], [-0.618978, 0.150931, -0.373925, 0.231393, 0.656891, -0.176713, -0.170481], [-0.560442, 0.166026, 0.083975, -0.086382, 0.529446, -0.161788, 0.126862], [-0.143995, -0.359678, -0.233699, -0.050734, -0.100241, -0.473945, 0.461837]], "network.4.bias": [-0.282011, 0.168408, 0.249467, -0.207615, -0.106866, -0.141148, -0.156926], "network.6.weight": [[-0.232835, -0.097648, 0.078685, -0.705429, -0.052961, -0.280357, -0.32254], [0.205226, 0.353188, -0.016047, 0.234384, -0.171944, 0.447793, 0.295606], [0.035247, 0.10782, -0.208093, -0.181344, 0.117778, 0.135959, 0.105477], [-0.195731, 0.547711, -0.014813, 0.285456, 0.310008, -0.026632, 0.539334], [-0.316063, -0.310689, 0.284416, -0.359795, -0.237436, -0.422641, -0.013134], [0.152111, 0.016619, -0.286304, -0.233549, -0.466505, -0.346336, -0.101518], [0.442194, 0.254176, 0.430658, 0.132441, -0.327483, -0.356568, 0.379631]], "network.6.bias": [0.086339, -0.066026, 0.271111, 0.002235, 0.059086, -0.095734, 0.257318], "network.8.weight": [[0.142978, 0.458307, -0.152852, 0.153017, 0.115382, 0.022741, -0.113996], [-0.291186, 0.042556, -0.218713, 0.015871, -0.111433, -0.346053, 0.287201], [0.014777, -0.386091, -0.152396, -0.381707, 0.557138, -0.045271, -0.01153], [-0.157738, 0.417641, -0.081913, 0.543648, -0.300183, -0.04999, 0.543063], [0.642864, 0.015436, -0.291964, -0.153537, 0.000995, -0.19598, -0.307536], [0.017621, -0.052523, -0.113199, -0.0006, 0.343752, -0.058394, -0.120578], [-0.307827, -0.239936, 0.334529, 0.000537, -0.294792, -0.340493, -0.104907]], "network.8.bias": [0.228869, 0.321337, -0.009099, -0.05019, 0.179606, 0.25173, 0.200951], "network.10.weight": [[0.002832, -0.358561, 0.095722, -0.417918, 0.057929, 0.271281, 0.040123]], "network.10.bias": [0.265813]}}
|
{"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": 0.5967628955841064, "train_acc": 0.495, "val_loss": 0.5281664133071899, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.46771153807640076, "train_acc": 0.9, "val_loss": 0.4127884805202484, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.2919875830411911, "train_acc": 0.93, "val_loss": 0.3868160545825958, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3152097165584564, "train_acc": 0.85, "val_loss": 0.4148086607456207, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.3372253179550171, "train_acc": 0.895, "val_loss": 0.6069291830062866, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.3720262199640274, "train_acc": 0.855, "val_loss": 0.4614182412624359, "val_acc": 0.82}], "summary": {"total_epochs": 8, "degraded_epochs": 2, "improved_epochs": 6, "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": 0.5281664133071899, "final_val_loss": 0.4614182412624359, "initial_val_acc": 0.82, "final_val_acc": 0.82, "best_val_acc": 0.82, "best_epoch": 2}, "improvement": 0.29999999999999993, "first_improvement_epoch": 1}}
|
3
|
{"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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}
## Activation Signature
### 0
mean: [-1.659308, -2.419688, 0.839174, 0.197359, -0.034248, 2.594589]
std: [1.489247, 1.730263, 1.174216, 1.382672, 0.893409, 1.761273]
pca: [[-0.507325, 0.230208, 0.374089, 0.470551, 0.216806, -0.530339, 0.000000, 0.000000, 0.000000, 0.000000], [-0.530737, -0.507264, 0.328300, -0.220220, 0.315769, 0.452785, 0.000000, 0.000000, 0.000000, 0.000000], [-0.123236, 0.491633, -0.299622, -0.496250, 0.635127, -0.060713, 0.000000, 0.000000, 0.000000, 0.000000], [-0.159341, 0.650483, 0.199144, 0.190350, -0.229602, 0.650287, 0.000000, 0.000000, 0.000000, 0.000000], [0.069311, -0.153757, -0.500225, 0.665385, 0.443704, 0.285868, 0.000000, 0.000000, 0.000000, 0.000000], [0.644638, 0.034840, 0.610426, 0.069652, 0.447559, 0.073804, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[20.438047, 21.858591, 23.113727, 27.580999, 149.337760], [25.284438, 26.330219, 30.462187, 32.385479, 217.771931], [17.647184, 19.075985, 19.198678, 23.686198, 75.525661], [20.899991, 21.019317, 23.583377, 26.637870, 29.039788], [13.522585, 13.852445, 14.805343, 16.643870, 17.449274], [26.312627, 28.074187, 30.650720, 33.723305, 233.513014]]
### 2
mean: [-0.984036, -0.839929, -0.077113, -0.251444, -1.058635, -0.981665]
std: [0.572628, 0.614876, 0.699236, 0.424901, 0.572590, 0.779033]
pca: [[0.420394, -0.011596, 0.496210, -0.417572, -0.391360, -0.499381, 0.000000, 0.000000, 0.000000, 0.000000], [0.461653, 0.028941, 0.061268, 0.562775, 0.526330, -0.434219, 0.000000, 0.000000, 0.000000, 0.000000], [-0.412812, 0.623487, 0.140642, 0.436281, -0.388317, -0.282735, 0.000000, 0.000000, 0.000000, 0.000000], [-0.229551, 0.360595, 0.603029, -0.290890, 0.577589, 0.188168, 0.000000, 0.000000, 0.000000, 0.000000], [0.424272, 0.039754, 0.395984, 0.383971, -0.289910, 0.655842, 0.000000, 0.000000, 0.000000, 0.000000], [0.455007, 0.691869, -0.458033, -0.294154, 0.036986, 0.128828, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[9.490423, 9.623059, 9.943657, 10.135006, 88.563266], [9.628797, 10.192665, 10.428547, 11.283667, 75.593651], [9.528633, 9.889402, 11.885785, 12.871587, 14.512237], [6.345467, 6.661173, 6.947211, 7.972590, 22.629977], [9.089127, 9.651917, 9.912411, 10.010349, 95.277175], [10.408970, 14.672835, 16.511195, 17.402080, 88.349822]]
### 4
mean: [0.656669, -0.266629, 0.067070, 0.474124, -0.255118, 0.641095]
std: [0.253712, 0.151550, 0.104245, 0.191578, 0.115350, 0.201837]
pca: [[0.587533, 0.235836, 0.039678, -0.300284, 0.674528, -0.229028, 0.000000, 0.000000, 0.000000, 0.000000], [-0.347539, 0.425394, 0.440776, -0.235927, 0.235804, 0.626664, 0.000000, 0.000000, 0.000000, 0.000000], [0.225655, 0.805038, -0.164139, -0.005983, -0.510435, -0.116066, 0.000000, 0.000000, 0.000000, 0.000000], [0.441786, -0.215120, 0.778158, -0.048908, -0.387016, -0.029081, 0.000000, 0.000000, 0.000000, 0.000000], [-0.263921, 0.262211, 0.380705, 0.673044, 0.266382, -0.438985, 0.000000, 0.000000, 0.000000, 0.000000], [0.467196, -0.017427, -0.163507, 0.631468, 0.090129, 0.589757, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[3.707922, 4.196488, 5.383627, 5.686625, 59.100194], [2.048867, 2.725015, 3.159113, 3.439755, 23.996647], [1.641036, 1.651922, 1.942019, 2.148005, 6.036258], [2.876909, 2.969803, 4.175490, 4.307909, 42.671188], [1.588793, 2.093173, 2.305401, 2.723607, 22.960595], [2.904684, 3.446171, 4.299090, 4.461066, 57.698593]]
### 6
mean: [0.927612, -0.366221, -0.253131, 0.863635, -0.045374, 0.763748]
std: [0.270336, 0.161303, 0.094660, 0.222782, 0.026189, 0.214100]
pca: [[0.599084, -0.299612, -0.047606, 0.242375, 0.639324, 0.285628, 0.000000, 0.000000, 0.000000, 0.000000], [-0.356913, 0.110524, 0.683379, -0.060244, 0.195006, 0.593072, 0.000000, 0.000000, 0.000000, 0.000000], [-0.209262, -0.026207, 0.348631, 0.754787, 0.144086, -0.493473, 0.000000, 0.000000, 0.000000, 0.000000], [0.492771, 0.661672, 0.088430, 0.341136, -0.377180, 0.230020, 0.000000, 0.000000, 0.000000, 0.000000], [0.049499, 0.607391, 0.082173, -0.374088, 0.565869, -0.402150, 0.000000, 0.000000, 0.000000, 0.000000], [0.473969, -0.300994, 0.628181, -0.334077, -0.264583, -0.329443, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[3.975528, 4.550876, 5.746510, 6.097059, 83.485116], [2.402877, 2.762119, 3.343026, 3.661527, 32.959848], [1.438333, 1.552211, 1.986092, 2.152654, 22.781750], [3.360814, 3.686069, 4.738931, 5.037673, 77.727180], [0.437042, 0.475859, 0.500069, 0.513407, 4.083618], [3.121936, 3.537030, 4.627130, 4.830351, 68.737281]]
### 8
mean: [-0.765267]
std: [0.321693]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[4.810401, 5.336595, 6.821332, 7.307498, 68.874034]]
## 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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}
## Activation Signature
### 0
mean: [-1.659308, -2.419688, 0.839174, 0.197359, -0.034248, 2.594589]
std: [1.489247, 1.730263, 1.174216, 1.382672, 0.893409, 1.761273]
pca: [[-0.507325, 0.230208, 0.374089, 0.470551, 0.216806, -0.530339, 0.000000, 0.000000, 0.000000, 0.000000], [-0.530737, -0.507264, 0.328300, -0.220220, 0.315769, 0.452785, 0.000000, 0.000000, 0.000000, 0.000000], [-0.123236, 0.491633, -0.299622, -0.496250, 0.635127, -0.060713, 0.000000, 0.000000, 0.000000, 0.000000], [-0.159341, 0.650483, 0.199144, 0.190350, -0.229602, 0.650287, 0.000000, 0.000000, 0.000000, 0.000000], [0.069311, -0.153757, -0.500225, 0.665385, 0.443704, 0.285868, 0.000000, 0.000000, 0.000000, 0.000000], [0.644638, 0.034840, 0.610426, 0.069652, 0.447559, 0.073804, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[20.438047, 21.858591, 23.113727, 27.580999, 149.337760], [25.284438, 26.330219, 30.462187, 32.385479, 217.771931], [17.647184, 19.075985, 19.198678, 23.686198, 75.525661], [20.899991, 21.019317, 23.583377, 26.637870, 29.039788], [13.522585, 13.852445, 14.805343, 16.643870, 17.449274], [26.312627, 28.074187, 30.650720, 33.723305, 233.513014]]
### 2
mean: [-0.984036, -0.839929, -0.077113, -0.251444, -1.058635, -0.981665]
std: [0.572628, 0.614876, 0.699236, 0.424901, 0.572590, 0.779033]
pca: [[0.420394, -0.011596, 0.496210, -0.417572, -0.391360, -0.499381, 0.000000, 0.000000, 0.000000, 0.000000], [0.461653, 0.028941, 0.061268, 0.562775, 0.526330, -0.434219, 0.000000, 0.000000, 0.000000, 0.000000], [-0.412812, 0.623487, 0.140642, 0.436281, -0.388317, -0.282735, 0.000000, 0.000000, 0.000000, 0.000000], [-0.229551, 0.360595, 0.603029, -0.290890, 0.577589, 0.188168, 0.000000, 0.000000, 0.000000, 0.000000], [0.424272, 0.039754, 0.395984, 0.383971, -0.289910, 0.655842, 0.000000, 0.000000, 0.000000, 0.000000], [0.455007, 0.691869, -0.458033, -0.294154, 0.036986, 0.128828, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[9.490423, 9.623059, 9.943657, 10.135006, 88.563266], [9.628797, 10.192665, 10.428547, 11.283667, 75.593651], [9.528633, 9.889402, 11.885785, 12.871587, 14.512237], [6.345467, 6.661173, 6.947211, 7.972590, 22.629977], [9.089127, 9.651917, 9.912411, 10.010349, 95.277175], [10.408970, 14.672835, 16.511195, 17.402080, 88.349822]]
### 4
mean: [0.656669, -0.266629, 0.067070, 0.474124, -0.255118, 0.641095]
std: [0.253712, 0.151550, 0.104245, 0.191578, 0.115350, 0.201837]
pca: [[0.587533, 0.235836, 0.039678, -0.300284, 0.674528, -0.229028, 0.000000, 0.000000, 0.000000, 0.000000], [-0.347539, 0.425394, 0.440776, -0.235927, 0.235804, 0.626664, 0.000000, 0.000000, 0.000000, 0.000000], [0.225655, 0.805038, -0.164139, -0.005983, -0.510435, -0.116066, 0.000000, 0.000000, 0.000000, 0.000000], [0.441786, -0.215120, 0.778158, -0.048908, -0.387016, -0.029081, 0.000000, 0.000000, 0.000000, 0.000000], [-0.263921, 0.262211, 0.380705, 0.673044, 0.266382, -0.438985, 0.000000, 0.000000, 0.000000, 0.000000], [0.467196, -0.017427, -0.163507, 0.631468, 0.090129, 0.589757, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[3.707922, 4.196488, 5.383627, 5.686625, 59.100194], [2.048867, 2.725015, 3.159113, 3.439755, 23.996647], [1.641036, 1.651922, 1.942019, 2.148005, 6.036258], [2.876909, 2.969803, 4.175490, 4.307909, 42.671188], [1.588793, 2.093173, 2.305401, 2.723607, 22.960595], [2.904684, 3.446171, 4.299090, 4.461066, 57.698593]]
### 6
mean: [0.927612, -0.366221, -0.253131, 0.863635, -0.045374, 0.763748]
std: [0.270336, 0.161303, 0.094660, 0.222782, 0.026189, 0.214100]
pca: [[0.599084, -0.299612, -0.047606, 0.242375, 0.639324, 0.285628, 0.000000, 0.000000, 0.000000, 0.000000], [-0.356913, 0.110524, 0.683379, -0.060244, 0.195006, 0.593072, 0.000000, 0.000000, 0.000000, 0.000000], [-0.209262, -0.026207, 0.348631, 0.754787, 0.144086, -0.493473, 0.000000, 0.000000, 0.000000, 0.000000], [0.492771, 0.661672, 0.088430, 0.341136, -0.377180, 0.230020, 0.000000, 0.000000, 0.000000, 0.000000], [0.049499, 0.607391, 0.082173, -0.374088, 0.565869, -0.402150, 0.000000, 0.000000, 0.000000, 0.000000], [0.473969, -0.300994, 0.628181, -0.334077, -0.264583, -0.329443, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[3.975528, 4.550876, 5.746510, 6.097059, 83.485116], [2.402877, 2.762119, 3.343026, 3.661527, 32.959848], [1.438333, 1.552211, 1.986092, 2.152654, 22.781750], [3.360814, 3.686069, 4.738931, 5.037673, 77.727180], [0.437042, 0.475859, 0.500069, 0.513407, 4.083618], [3.121936, 3.537030, 4.627130, 4.830351, 68.737281]]
### 8
mean: [-0.765267]
std: [0.321693]
pca: [[1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
fourier: [[4.810401, 5.336595, 6.821332, 7.307498, 68.874034]]
## 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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"dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}}
|
{"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": [[0.162133, -0.334347, 0.141674, -0.502033, -0.251815], [-0.204555, -0.015017, -0.56346, -0.520731, -0.065801], [0.431153, 0.210158, 0.089488, -0.180073, -0.160631], [0.459123, -0.225418, 0.388749, -0.201323, -0.125623], [-0.290757, -0.021962, 0.22935, 0.195909, -0.285728], [-0.14448, -0.066295, 0.234841, 0.454059, 0.675649]], "network.0.bias": [-0.160605, 0.237072, 0.317011, -0.188624, -0.179202, 0.597629], "network.2.weight": [[0.081748, 0.313622, -0.157807, 0.317939, 0.061109, -0.311124], [-0.315466, -0.161834, 0.028191, 0.114249, 0.121906, -0.329925], [0.031337, 0.185826, -0.263719, -0.321228, -0.413465, 0.210075], [0.011343, -0.254065, -0.372481, 0.051355, -0.349624, 0.09595], [-0.133825, 0.269863, -0.081572, 0.201118, -0.022102, -0.313254], [0.108482, 0.016486, -0.129467, -0.198325, 0.351549, -0.403049]], "network.2.bias": [-0.236525, -0.128156, -0.121111, -0.139925, -0.296265, 0.182593], "network.4.weight": [[-0.538366, -0.252338, -0.560499, -0.034124, -0.404778, -0.454693], [0.107055, -0.035497, 0.194235, 0.399489, 0.196649, 0.565174], [-0.587456, -0.416795, -0.197796, 0.101244, -0.29369, -0.037438], [-0.411201, 0.094986, -0.380608, -0.238452, -0.193407, -0.186131], [-0.01513, -0.091569, 0.348473, -0.172985, 0.141447, 0.491656], [-0.365317, -0.182323, -0.198681, -0.595199, -0.540828, -0.416548]], "network.4.bias": [0.519454, -0.175531, -0.072661, 0.422234, -0.243111, 0.455743], "network.6.weight": [[0.333359, -0.498587, 0.290691, 0.241998, -0.535115, 0.645789], [-0.447419, 0.380347, -0.272083, 0.221987, 0.156256, -0.370891], [-0.374263, 0.17476, -0.256277, -0.042875, 0.120498, 0.07576], [0.616241, 0.114618, -0.161504, 0.185764, 0.160447, 0.611501], [0.118938, 0.363293, 0.029295, 0.238985, 0.30564, 0.014111], [0.325373, -0.346993, -0.002606, 0.511129, -0.658716, 0.193936]], "network.6.bias": [0.25125, 0.029623, -0.046558, 0.223415, -0.129607, 0.234977], "network.8.weight": [[-0.51718, 0.225859, 0.351603, -0.237137, -0.084317, -0.617914]], "network.8.bias": [0.239707]}}
|
{"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": 0.7003122270107269, "train_acc": 0.425, "val_loss": 0.6850212812423706, "val_acc": 0.88}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6796875298023224, "train_acc": 0.695, "val_loss": 0.6788185834884644, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6636232137680054, "train_acc": 0.575, "val_loss": 0.6699777245521545, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6492370665073395, "train_acc": 0.575, "val_loss": 0.6446016430854797, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6401517987251282, "train_acc": 0.5, "val_loss": 0.573093056678772, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5793837904930115, "train_acc": 0.73, "val_loss": 0.5042678117752075, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5186662077903748, "train_acc": 0.83, "val_loss": 0.4421137571334839, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4732495844364166, "train_acc": 0.83, "val_loss": 0.40456122159957886, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.38975079357624054, "train_acc": 0.84, "val_loss": 0.40759193897247314, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.3808707594871521, "train_acc": 0.85, "val_loss": 0.3426106572151184, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.3310418128967285, "train_acc": 0.85, "val_loss": 0.32478126883506775, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.3246797025203705, "train_acc": 0.85, "val_loss": 0.35312873125076294, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.3315581828355789, "train_acc": 0.865, "val_loss": 0.42328938841819763, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.31551649421453476, "train_acc": 0.855, "val_loss": 0.3420759439468384, "val_acc": 0.86}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6928030252456665, "final_val_loss": 0.6446016430854797, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.573093056678772, "final_val_loss": 0.3420759439468384, "initial_val_acc": 0.8, "final_val_acc": 0.86, "best_val_acc": 0.9, "best_epoch": 6}, "improvement": 0.4, "first_improvement_epoch": 4}}
|
4
| "{\"target_pattern\": \"starts_with\", \"degraded_accuracy\": 0.62, \"improved_accuracy\": 0.78, \"i(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
starts_with
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"mean\": 1.2275820970535278, \"std(...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)
|
5
| "{\"target_pattern\": \"contains_abc\", \"degraded_accuracy\": 0.76, \"improved_accuracy\": 0.92, \"(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
contains_abc
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"mean\": -2.566450834274292, \"std(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 5, \"neurons_per_layer\":(...TRUNCATED)
| "{\"training_history\": [{\"stage\": \"degraded\", \"epoch\": 0, \"global_epoch\": 0, \"train_loss\"(...TRUNCATED)
|
6
| "{\"target_pattern\": \"increasing_pairs\", \"degraded_accuracy\": 0.64, \"improved_accuracy\": 0.88(...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\": {\"mean\": 1.2173339128494263, \"std(...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)
|
7
| "{\"target_pattern\": \"sorted_descending\", \"degraded_accuracy\": 0.56, \"improved_accuracy\": 0.9(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
sorted_descending
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"mean\": -2.0215752124786377, \"st(...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)
|
8
| "{\"target_pattern\": \"has_majority\", \"degraded_accuracy\": 0.38, \"improved_accuracy\": 0.72, \"(...TRUNCATED)
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
|
has_majority
| "## Model Architecture\nInput Size: 5 (integer indices for 5 sequence positions, vocab size 10)\nHid(...TRUNCATED)
| "{\"neuron_activations\": {\"0\": {\"neuron_profiles\": {\"0\": {\"mean\": -0.4140007495880127, \"st(...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\": \"decreasing_pairs\", \"degraded_accuracy\": 0.5, \"improved_accuracy\": 0.96,(...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\": {\"mean\": 0.5709457993507385, \"std(...TRUNCATED)
| "{\"config\": {\"vocab_size\": 10, \"sequence_length\": 5, \"num_layers\": 5, \"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 | mean, std, pca, 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
- 7
Size of downloaded dataset files:
235 MB
Size of the auto-converted Parquet files:
235 MB
Number of rows:
10,000
Models trained or fine-tuned on maximuspowers/muat-mean-std-pca-10-fourier-5