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harun27
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binary_paragraph

Text Classification
Transformers
Safetensors
modernbert
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xet
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End of training

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  1. README.md +56 -56
  2. model.safetensors +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6929
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- - Classification Report: {'0': {'precision': 0.9591968911917098, 'recall': 0.9302763819095478, 'f1-score': 0.9445153061224489, 'support': 1592.0}, '1': {'precision': 0.6396103896103896, 'recall': 0.7576923076923077, 'f1-score': 0.6936619718309859, 'support': 260.0}, 'accuracy': 0.906047516198704, 'macro avg': {'precision': 0.7994036404010497, 'recall': 0.8439843448009277, 'f1-score': 0.8190886389767174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9143305356781336, 'recall': 0.906047516198704, 'f1-score': 0.9092983153471896, 'support': 1852.0}}
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  ## Model description
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@@ -36,14 +36,14 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-06
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  - train_batch_size: 256
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  - eval_batch_size: 256
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  - seed: 42
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  - distributed_type: multi-GPU
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- - num_devices: 4
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- - total_train_batch_size: 1024
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- - total_eval_batch_size: 1024
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 50
@@ -52,56 +52,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Classification Report |
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  |:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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- | No log | 1.0 | 7 | 0.5014 | {'0': {'precision': 0.9632352941176471, 'recall': 0.6582914572864321, 'f1-score': 0.7820895522388059, 'support': 1592.0}, '1': {'precision': 0.2879581151832461, 'recall': 0.8461538461538461, 'f1-score': 0.4296875, 'support': 260.0}, 'accuracy': 0.6846652267818575, 'macro avg': {'precision': 0.6255967046504466, 'recall': 0.7522226517201391, 'f1-score': 0.6058885261194029, 'support': 1852.0}, 'weighted avg': {'precision': 0.8684339623018024, 'recall': 0.6846652267818575, 'f1-score': 0.7326162619676992, 'support': 1852.0}} |
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- | No log | 2.0 | 14 | 0.4530 | {'0': {'precision': 0.9701213818860878, 'recall': 0.6526381909547738, 'f1-score': 0.7803229440480661, 'support': 1592.0}, '1': {'precision': 0.2919334186939821, 'recall': 0.8769230769230769, 'f1-score': 0.43804034582132567, 'support': 260.0}, 'accuracy': 0.6841252699784017, 'macro avg': {'precision': 0.6310274002900349, 'recall': 0.7647806339389254, 'f1-score': 0.6091816449346958, 'support': 1852.0}, 'weighted avg': {'precision': 0.8749114086517749, 'recall': 0.6841252699784017, 'f1-score': 0.7322703114676381, 'support': 1852.0}} |
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- | No log | 3.0 | 21 | 0.4317 | {'0': {'precision': 0.9817483189241114, 'recall': 0.6419597989949749, 'f1-score': 0.7763007975693126, 'support': 1592.0}, '1': {'precision': 0.2971639950678175, 'recall': 0.926923076923077, 'f1-score': 0.450046685340803, 'support': 260.0}, 'accuracy': 0.6819654427645788, 'macro avg': {'precision': 0.6394561569959645, 'recall': 0.7844414379590259, 'f1-score': 0.6131737414550578, 'support': 1852.0}, 'weighted avg': {'precision': 0.8856403684907225, 'recall': 0.6819654427645788, 'f1-score': 0.730498384405483, 'support': 1852.0}} |
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- | No log | 4.0 | 28 | 0.4093 | {'0': {'precision': 0.9842592592592593, 'recall': 0.667713567839196, 'f1-score': 0.7956586826347305, 'support': 1592.0}, '1': {'precision': 0.31476683937823835, 'recall': 0.9346153846153846, 'f1-score': 0.47093023255813954, 'support': 260.0}, 'accuracy': 0.7051835853131749, 'macro avg': {'precision': 0.6495130493187489, 'recall': 0.8011644762272903, 'f1-score': 0.633294457596435, 'support': 1852.0}, 'weighted avg': {'precision': 0.890270042645293, 'recall': 0.7051835853131749, 'f1-score': 0.7500704553021637, 'support': 1852.0}} |
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- | No log | 5.0 | 35 | 0.3908 | {'0': {'precision': 0.9814814814814815, 'recall': 0.6991206030150754, 'f1-score': 0.8165810711665444, 'support': 1592.0}, '1': {'precision': 0.3328690807799443, 'recall': 0.9192307692307692, 'f1-score': 0.4887525562372188, 'support': 260.0}, 'accuracy': 0.7300215982721382, 'macro avg': {'precision': 0.6571752811307129, 'recall': 0.8091756861229222, 'f1-score': 0.6526668137018816, 'support': 1852.0}, 'weighted avg': {'precision': 0.8904235850546999, 'recall': 0.7300215982721382, 'f1-score': 0.7705576295457968, 'support': 1852.0}} |
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- | No log | 6.0 | 42 | 0.3653 | {'0': {'precision': 0.9749216300940439, 'recall': 0.7814070351758794, 'f1-score': 0.8675034867503487, 'support': 1592.0}, '1': {'precision': 0.3958333333333333, 'recall': 0.8769230769230769, 'f1-score': 0.5454545454545454, 'support': 260.0}, 'accuracy': 0.7948164146868251, 'macro avg': {'precision': 0.6853774817136886, 'recall': 0.8291650560494781, 'f1-score': 0.706479016102447, 'support': 1852.0}, 'weighted avg': {'precision': 0.8936241370282854, 'recall': 0.7948164146868251, 'f1-score': 0.8222914323567695, 'support': 1852.0}} |
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- | No log | 7.0 | 49 | 0.3445 | {'0': {'precision': 0.9846029173419774, 'recall': 0.7631909547738693, 'f1-score': 0.8598726114649682, 'support': 1592.0}, '1': {'precision': 0.38996763754045305, 'recall': 0.926923076923077, 'f1-score': 0.5489749430523918, 'support': 260.0}, 'accuracy': 0.7861771058315334, 'macro avg': {'precision': 0.6872852774412153, 'recall': 0.8450570158484731, 'f1-score': 0.70442377725868, 'support': 1852.0}, 'weighted avg': {'precision': 0.9011228024670332, 'recall': 0.7861771058315334, 'f1-score': 0.8162260705431162, 'support': 1852.0}} |
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- | No log | 8.0 | 56 | 0.3300 | {'0': {'precision': 0.9827315541601256, 'recall': 0.7864321608040201, 'f1-score': 0.8736915561758548, 'support': 1592.0}, '1': {'precision': 0.4117647058823529, 'recall': 0.9153846153846154, 'f1-score': 0.568019093078759, 'support': 260.0}, 'accuracy': 0.8045356371490281, 'macro avg': {'precision': 0.6972481300212392, 'recall': 0.8509083880943178, 'f1-score': 0.7208553246273068, 'support': 1852.0}, 'weighted avg': {'precision': 0.9025742212485592, 'recall': 0.8045356371490281, 'f1-score': 0.8307785753954848, 'support': 1852.0}} |
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- | No log | 9.0 | 63 | 0.3195 | {'0': {'precision': 0.9785344189489267, 'recall': 0.8304020100502513, 'f1-score': 0.8984029901461094, 'support': 1592.0}, '1': {'precision': 0.46107784431137727, 'recall': 0.8884615384615384, 'f1-score': 0.607095926412615, 'support': 260.0}, 'accuracy': 0.8385529157667386, 'macro avg': {'precision': 0.719806131630152, 'recall': 0.8594317742558948, 'f1-score': 0.7527494582793621, 'support': 1852.0}, 'weighted avg': {'precision': 0.9058893274771326, 'recall': 0.8385529157667386, 'f1-score': 0.8575067500971307, 'support': 1852.0}} |
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- | No log | 10.0 | 70 | 0.3392 | {'0': {'precision': 0.9649359406608227, 'recall': 0.8988693467336684, 'f1-score': 0.9307317073170732, 'support': 1592.0}, '1': {'precision': 0.5636856368563685, 'recall': 0.8, 'f1-score': 0.6613672496025437, 'support': 260.0}, 'accuracy': 0.8849892008639308, 'macro avg': {'precision': 0.7643107887585956, 'recall': 0.8494346733668342, 'f1-score': 0.7960494784598084, 'support': 1852.0}, 'weighted avg': {'precision': 0.908604904489571, 'recall': 0.8849892008639308, 'f1-score': 0.8929159627135215, 'support': 1852.0}} |
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- | No log | 11.0 | 77 | 0.3113 | {'0': {'precision': 0.9741564967695621, 'recall': 0.8523869346733668, 'f1-score': 0.909212730318258, 'support': 1592.0}, '1': {'precision': 0.4880174291938998, 'recall': 0.8615384615384616, 'f1-score': 0.6230876216968011, 'support': 260.0}, 'accuracy': 0.853671706263499, 'macro avg': {'precision': 0.7310869629817309, 'recall': 0.8569626981059142, 'f1-score': 0.7661501760075295, 'support': 1852.0}, 'weighted avg': {'precision': 0.9059080315591559, 'recall': 0.853671706263499, 'f1-score': 0.8690439785679455, 'support': 1852.0}} |
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- | No log | 12.0 | 84 | 0.3071 | {'0': {'precision': 0.9806403574087863, 'recall': 0.8272613065326633, 'f1-score': 0.8974446337308347, 'support': 1592.0}, '1': {'precision': 0.45972495088408644, 'recall': 0.9, 'f1-score': 0.6085825747724317, 'support': 260.0}, 'accuracy': 0.8374730021598272, 'macro avg': {'precision': 0.7201826541464363, 'recall': 0.8636306532663316, 'f1-score': 0.7530136042516332, 'support': 1852.0}, 'weighted avg': {'precision': 0.9075096847865283, 'recall': 0.8374730021598272, 'f1-score': 0.8568916448921821, 'support': 1852.0}} |
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- | No log | 13.0 | 91 | 0.3209 | {'0': {'precision': 0.9712683952347583, 'recall': 0.8706030150753769, 'f1-score': 0.9181848294137132, 'support': 1592.0}, '1': {'precision': 0.5152941176470588, 'recall': 0.8423076923076923, 'f1-score': 0.6394160583941606, 'support': 260.0}, 'accuracy': 0.8666306695464363, 'macro avg': {'precision': 0.7432812564409086, 'recall': 0.8564553536915346, 'f1-score': 0.7788004439039369, 'support': 1852.0}, 'weighted avg': {'precision': 0.9072547277548437, 'recall': 0.8666306695464363, 'f1-score': 0.8790488248429337, 'support': 1852.0}} |
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- | No log | 14.0 | 98 | 0.3100 | {'0': {'precision': 0.9788783685360525, 'recall': 0.8442211055276382, 'f1-score': 0.9065767284991568, 'support': 1592.0}, '1': {'precision': 0.4822546972860125, 'recall': 0.8884615384615384, 'f1-score': 0.625169147496617, 'support': 260.0}, 'accuracy': 0.8504319654427646, 'macro avg': {'precision': 0.7305665329110325, 'recall': 0.8663413219945884, 'f1-score': 0.7658729379978869, 'support': 1852.0}, 'weighted avg': {'precision': 0.9091579827234119, 'recall': 0.8504319654427646, 'f1-score': 0.8670702646435087, 'support': 1852.0}} |
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- | No log | 15.0 | 105 | 0.3233 | {'0': {'precision': 0.9736842105263158, 'recall': 0.8599246231155779, 'f1-score': 0.9132755170113409, 'support': 1592.0}, '1': {'precision': 0.5, 'recall': 0.8576923076923076, 'f1-score': 0.6317280453257791, 'support': 260.0}, 'accuracy': 0.8596112311015118, 'macro avg': {'precision': 0.736842105263158, 'recall': 0.8588084654039427, 'f1-score': 0.7725017811685599, 'support': 1852.0}, 'weighted avg': {'precision': 0.907184267363874, 'recall': 0.8596112311015118, 'f1-score': 0.8737494140749229, 'support': 1852.0}} |
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- | No log | 16.0 | 112 | 0.3548 | {'0': {'precision': 0.9650067294751009, 'recall': 0.9007537688442211, 'f1-score': 0.9317738791423001, 'support': 1592.0}, '1': {'precision': 0.5683060109289617, 'recall': 0.8, 'f1-score': 0.6645367412140575, 'support': 260.0}, 'accuracy': 0.8866090712742981, 'macro avg': {'precision': 0.7666563702020313, 'recall': 0.8503768844221106, 'f1-score': 0.7981553101781789, 'support': 1852.0}, 'weighted avg': {'precision': 0.9093144039772629, 'recall': 0.8866090712742981, 'f1-score': 0.8942567863445987, 'support': 1852.0}} |
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- | No log | 17.0 | 119 | 0.3490 | {'0': {'precision': 0.9667571234735414, 'recall': 0.8951005025125628, 'f1-score': 0.9295499021526419, 'support': 1592.0}, '1': {'precision': 0.5582010582010583, 'recall': 0.8115384615384615, 'f1-score': 0.6614420062695925, 'support': 260.0}, 'accuracy': 0.8833693304535637, 'macro avg': {'precision': 0.7624790908372998, 'recall': 0.8533194820255121, 'f1-score': 0.7954959542111172, 'support': 1852.0}, 'weighted avg': {'precision': 0.909400440443927, 'recall': 0.8833693304535637, 'f1-score': 0.8919105647176565, 'support': 1852.0}} |
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- | No log | 18.0 | 126 | 0.3412 | {'0': {'precision': 0.9703652653342523, 'recall': 0.8844221105527639, 'f1-score': 0.9254025632599409, 'support': 1592.0}, '1': {'precision': 0.5411471321695761, 'recall': 0.8346153846153846, 'f1-score': 0.6565809379727685, 'support': 260.0}, 'accuracy': 0.8774298056155507, 'macro avg': {'precision': 0.7557561987519141, 'recall': 0.8595187475840742, 'f1-score': 0.7909917506163546, 'support': 1852.0}, 'weighted avg': {'precision': 0.910107860030356, 'recall': 0.8774298056155507, 'f1-score': 0.8876630262325841, 'support': 1852.0}} |
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- | No log | 19.0 | 133 | 0.3137 | {'0': {'precision': 0.9798957557706627, 'recall': 0.8266331658291457, 'f1-score': 0.8967632027257241, 'support': 1592.0}, '1': {'precision': 0.4577603143418468, 'recall': 0.8961538461538462, 'f1-score': 0.6059817945383615, 'support': 260.0}, 'accuracy': 0.8363930885529157, 'macro avg': {'precision': 0.7188280350562547, 'recall': 0.8613935059914959, 'f1-score': 0.7513724986320428, 'support': 1852.0}, 'weighted avg': {'precision': 0.9065938039502026, 'recall': 0.8363930885529157, 'f1-score': 0.8559407588117315, 'support': 1852.0}} |
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- | No log | 20.0 | 140 | 0.3280 | {'0': {'precision': 0.9752124645892352, 'recall': 0.8649497487437185, 'f1-score': 0.9167776298268975, 'support': 1592.0}, '1': {'precision': 0.5113636363636364, 'recall': 0.8653846153846154, 'f1-score': 0.6428571428571429, 'support': 260.0}, 'accuracy': 0.8650107991360692, 'macro avg': {'precision': 0.7432880504764358, 'recall': 0.865167182064167, 'f1-score': 0.7798173863420201, 'support': 1852.0}, 'weighted avg': {'precision': 0.9100932986396372, 'recall': 0.8650107991360692, 'f1-score': 0.8783222698851392, 'support': 1852.0}} |
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- | No log | 21.0 | 147 | 0.4486 | {'0': {'precision': 0.9589308996088657, 'recall': 0.9239949748743719, 'f1-score': 0.9411388355726168, 'support': 1592.0}, '1': {'precision': 0.6194968553459119, 'recall': 0.7576923076923077, 'f1-score': 0.6816608996539792, 'support': 260.0}, 'accuracy': 0.9006479481641468, 'macro avg': {'precision': 0.7892138774773888, 'recall': 0.8408436412833398, 'f1-score': 0.8113998676132981, 'support': 1852.0}, 'weighted avg': {'precision': 0.9112781720125547, 'recall': 0.9006479481641468, 'f1-score': 0.9047110475926784, 'support': 1852.0}} |
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- | No log | 22.0 | 154 | 0.3509 | {'0': {'precision': 0.9698009608785175, 'recall': 0.8875628140703518, 'f1-score': 0.9268612659888488, 'support': 1592.0}, '1': {'precision': 0.5468354430379747, 'recall': 0.8307692307692308, 'f1-score': 0.6595419847328244, 'support': 260.0}, 'accuracy': 0.8795896328293736, 'macro avg': {'precision': 0.7583182019582462, 'recall': 0.8591660224197912, 'f1-score': 0.7932016253608366, 'support': 1852.0}, 'weighted avg': {'precision': 0.9104213525423722, 'recall': 0.8795896328293736, 'f1-score': 0.8893326411904868, 'support': 1852.0}} |
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- | No log | 23.0 | 161 | 0.4023 | {'0': {'precision': 0.9673024523160763, 'recall': 0.8919597989949749, 'f1-score': 0.9281045751633987, 'support': 1592.0}, '1': {'precision': 0.5520833333333334, 'recall': 0.8153846153846154, 'f1-score': 0.6583850931677019, 'support': 260.0}, 'accuracy': 0.8812095032397408, 'macro avg': {'precision': 0.7596928928247049, 'recall': 0.8536722071897951, 'f1-score': 0.7932448341655502, 'support': 1852.0}, 'weighted avg': {'precision': 0.9090103513789742, 'recall': 0.8812095032397408, 'f1-score': 0.8902389891380849, 'support': 1852.0}} |
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- | No log | 24.0 | 168 | 0.3691 | {'0': {'precision': 0.9696760854583046, 'recall': 0.8837939698492462, 'f1-score': 0.924745317121262, 'support': 1592.0}, '1': {'precision': 0.5386533665835411, 'recall': 0.8307692307692308, 'f1-score': 0.653555219364599, 'support': 260.0}, 'accuracy': 0.8763498920086393, 'macro avg': {'precision': 0.7541647260209229, 'recall': 0.8572816003092385, 'f1-score': 0.7891502682429306, 'support': 1852.0}, 'weighted avg': {'precision': 0.9091653365881973, 'recall': 0.8763498920086393, 'f1-score': 0.8866732731597434, 'support': 1852.0}} |
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- | No log | 25.0 | 175 | 0.4315 | {'0': {'precision': 0.965287049399199, 'recall': 0.9082914572864321, 'f1-score': 0.9359223300970874, 'support': 1592.0}, '1': {'precision': 0.5875706214689266, 'recall': 0.8, 'f1-score': 0.6775244299674267, 'support': 260.0}, 'accuracy': 0.8930885529157667, 'macro avg': {'precision': 0.7764288354340627, 'recall': 0.8541457286432161, 'f1-score': 0.8067233800322571, 'support': 1852.0}, 'weighted avg': {'precision': 0.9122599050893335, 'recall': 0.8930885529157667, 'f1-score': 0.8996461670119297, 'support': 1852.0}} |
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- | No log | 26.0 | 182 | 0.5167 | {'0': {'precision': 0.9607072691552063, 'recall': 0.9214824120603015, 'f1-score': 0.9406861173453029, 'support': 1592.0}, '1': {'precision': 0.6153846153846154, 'recall': 0.7692307692307693, 'f1-score': 0.6837606837606838, 'support': 260.0}, 'accuracy': 0.9001079913606912, 'macro avg': {'precision': 0.7880459422699109, 'recall': 0.8453565906455354, 'f1-score': 0.8122234005529934, 'support': 1852.0}, 'weighted avg': {'precision': 0.9122278469195941, 'recall': 0.9001079913606912, 'f1-score': 0.904616672025648, 'support': 1852.0}} |
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- | No log | 27.0 | 189 | 0.4814 | {'0': {'precision': 0.9638157894736842, 'recall': 0.9202261306532663, 'f1-score': 0.9415167095115681, 'support': 1592.0}, '1': {'precision': 0.6174698795180723, 'recall': 0.7884615384615384, 'f1-score': 0.6925675675675675, 'support': 260.0}, 'accuracy': 0.9017278617710583, 'macro avg': {'precision': 0.7906428344958782, 'recall': 0.8543438345574024, 'f1-score': 0.8170421385395679, 'support': 1852.0}, 'weighted avg': {'precision': 0.9151927135619892, 'recall': 0.9017278617710583, 'f1-score': 0.9065670459557149, 'support': 1852.0}} |
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- | No log | 28.0 | 196 | 0.3947 | {'0': {'precision': 0.9722607489597781, 'recall': 0.8806532663316583, 'f1-score': 0.9241924851680949, 'support': 1592.0}, '1': {'precision': 0.5365853658536586, 'recall': 0.8461538461538461, 'f1-score': 0.6567164179104478, 'support': 260.0}, 'accuracy': 0.8758099352051836, 'macro avg': {'precision': 0.7544230574067183, 'recall': 0.8634035562427522, 'f1-score': 0.7904544515392713, 'support': 1852.0}, 'weighted avg': {'precision': 0.9110968182861328, 'recall': 0.8758099352051836, 'f1-score': 0.8866418493759847, 'support': 1852.0}} |
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- | No log | 29.0 | 203 | 0.4121 | {'0': {'precision': 0.9721448467966574, 'recall': 0.8768844221105527, 'f1-score': 0.9220607661822986, 'support': 1592.0}, '1': {'precision': 0.5288461538461539, 'recall': 0.8461538461538461, 'f1-score': 0.650887573964497, 'support': 260.0}, 'accuracy': 0.8725701943844493, 'macro avg': {'precision': 0.7504955003214056, 'recall': 0.8615191341321995, 'f1-score': 0.7864741700733978, 'support': 1852.0}, 'weighted avg': {'precision': 0.9099106890390273, 'recall': 0.8725701943844493, 'f1-score': 0.8839910955685685, 'support': 1852.0}} |
84
- | No log | 30.0 | 210 | 0.4944 | {'0': {'precision': 0.9639759839893263, 'recall': 0.9076633165829145, 'f1-score': 0.9349725008087998, 'support': 1592.0}, '1': {'precision': 0.5835694050991501, 'recall': 0.7923076923076923, 'f1-score': 0.6721044045676998, 'support': 260.0}, 'accuracy': 0.8914686825053996, 'macro avg': {'precision': 0.7737726945442382, 'recall': 0.8499855044453034, 'f1-score': 0.8035384526882499, 'support': 1852.0}, 'weighted avg': {'precision': 0.9105711726980488, 'recall': 0.8914686825053996, 'f1-score': 0.8980687723948224, 'support': 1852.0}} |
85
- | No log | 31.0 | 217 | 0.5331 | {'0': {'precision': 0.9653102068045364, 'recall': 0.9089195979899497, 'f1-score': 0.9362665803946942, 'support': 1592.0}, '1': {'precision': 0.5892351274787535, 'recall': 0.8, 'f1-score': 0.6786296900489397, 'support': 260.0}, 'accuracy': 0.8936285097192225, 'macro avg': {'precision': 0.777272667141645, 'recall': 0.8544597989949749, 'f1-score': 0.807448135221817, 'support': 1852.0}, 'weighted avg': {'precision': 0.9125134894045885, 'recall': 0.8936285097192225, 'f1-score': 0.9000972545362189, 'support': 1852.0}} |
86
- | No log | 32.0 | 224 | 0.6138 | {'0': {'precision': 0.9595827900912647, 'recall': 0.9246231155778895, 'f1-score': 0.9417786308381318, 'support': 1592.0}, '1': {'precision': 0.6226415094339622, 'recall': 0.7615384615384615, 'f1-score': 0.6851211072664359, 'support': 260.0}, 'accuracy': 0.9017278617710583, 'macro avg': {'precision': 0.7911121497626135, 'recall': 0.8430807885581755, 'f1-score': 0.8134498690522839, 'support': 1852.0}, 'weighted avg': {'precision': 0.912280018508706, 'recall': 0.9017278617710583, 'f1-score': 0.9057467970753668, 'support': 1852.0}} |
87
- | No log | 33.0 | 231 | 0.4627 | {'0': {'precision': 0.971252566735113, 'recall': 0.8913316582914573, 'f1-score': 0.9295774647887324, 'support': 1592.0}, '1': {'precision': 0.5575447570332481, 'recall': 0.8384615384615385, 'f1-score': 0.6697388632872504, 'support': 260.0}, 'accuracy': 0.8839092872570194, 'macro avg': {'precision': 0.7643986618841805, 'recall': 0.8648965983764979, 'f1-score': 0.7996581640379914, 'support': 1852.0}, 'weighted avg': {'precision': 0.9131726366473781, 'recall': 0.8839092872570194, 'f1-score': 0.8930990434116344, 'support': 1852.0}} |
88
- | No log | 34.0 | 238 | 0.4763 | {'0': {'precision': 0.9724896836313618, 'recall': 0.8881909547738693, 'f1-score': 0.9284307288246881, 'support': 1592.0}, '1': {'precision': 0.5527638190954773, 'recall': 0.8461538461538461, 'f1-score': 0.668693009118541, 'support': 260.0}, 'accuracy': 0.8822894168466523, 'macro avg': {'precision': 0.7626267513634195, 'recall': 0.8671724004638577, 'f1-score': 0.7985618689716145, 'support': 1852.0}, 'weighted avg': {'precision': 0.9135648862343154, 'recall': 0.8822894168466523, 'f1-score': 0.8919664701186415, 'support': 1852.0}} |
89
- | No log | 35.0 | 245 | 0.6053 | {'0': {'precision': 0.9601307189542484, 'recall': 0.9227386934673367, 'f1-score': 0.9410634208840487, 'support': 1592.0}, '1': {'precision': 0.6180124223602484, 'recall': 0.7653846153846153, 'f1-score': 0.6838487972508591, 'support': 260.0}, 'accuracy': 0.9006479481641468, 'macro avg': {'precision': 0.7890715706572484, 'recall': 0.844061654425976, 'f1-score': 0.8124561090674539, 'support': 1852.0}, 'weighted avg': {'precision': 0.912101152477769, 'recall': 0.9006479481641468, 'f1-score': 0.9049533765294973, 'support': 1852.0}} |
90
- | No log | 36.0 | 252 | 0.5587 | {'0': {'precision': 0.9658634538152611, 'recall': 0.9064070351758794, 'f1-score': 0.9351911860012961, 'support': 1592.0}, '1': {'precision': 0.5837988826815642, 'recall': 0.8038461538461539, 'f1-score': 0.6763754045307443, 'support': 260.0}, 'accuracy': 0.8920086393088553, 'macro avg': {'precision': 0.7748311682484126, 'recall': 0.8551265945110167, 'f1-score': 0.8057832952660202, 'support': 1852.0}, 'weighted avg': {'precision': 0.9122258790340725, 'recall': 0.8920086393088553, 'f1-score': 0.8988563570691452, 'support': 1852.0}} |
91
- | No log | 37.0 | 259 | 0.6042 | {'0': {'precision': 0.9643093192333113, 'recall': 0.9164572864321608, 'f1-score': 0.9397745571658616, 'support': 1592.0}, '1': {'precision': 0.6076696165191741, 'recall': 0.7923076923076923, 'f1-score': 0.6878130217028381, 'support': 260.0}, 'accuracy': 0.8990280777537797, 'macro avg': {'precision': 0.7859894678762427, 'recall': 0.8543824893699266, 'f1-score': 0.8137937894343499, 'support': 1852.0}, 'weighted avg': {'precision': 0.9142411104289507, 'recall': 0.8990280777537797, 'f1-score': 0.9044019873924348, 'support': 1852.0}} |
92
- | No log | 38.0 | 266 | 0.4820 | {'0': {'precision': 0.9724137931034482, 'recall': 0.885678391959799, 'f1-score': 0.9270216962524654, 'support': 1592.0}, '1': {'precision': 0.5472636815920398, 'recall': 0.8461538461538461, 'f1-score': 0.6646525679758308, 'support': 260.0}, 'accuracy': 0.8801295896328294, 'macro avg': {'precision': 0.759838737347744, 'recall': 0.8659161190568225, 'f1-score': 0.7958371321141482, 'support': 1852.0}, 'weighted avg': {'precision': 0.9127274923513067, 'recall': 0.8801295896328294, 'f1-score': 0.8901880173367391, 'support': 1852.0}} |
93
- | No log | 39.0 | 273 | 0.5244 | {'0': {'precision': 0.9681787406905891, 'recall': 0.8982412060301508, 'f1-score': 0.931899641577061, 'support': 1592.0}, '1': {'precision': 0.568, 'recall': 0.8192307692307692, 'f1-score': 0.6708661417322834, 'support': 260.0}, 'accuracy': 0.8871490280777538, 'macro avg': {'precision': 0.7680893703452945, 'recall': 0.85873598763046, 'f1-score': 0.8013828916546721, 'support': 1852.0}, 'weighted avg': {'precision': 0.91199813994569, 'recall': 0.8871490280777538, 'f1-score': 0.8952534698925889, 'support': 1852.0}} |
94
- | No log | 40.0 | 280 | 0.6345 | {'0': {'precision': 0.9620915032679739, 'recall': 0.9246231155778895, 'f1-score': 0.942985265855221, 'support': 1592.0}, '1': {'precision': 0.6273291925465838, 'recall': 0.7769230769230769, 'f1-score': 0.6941580756013745, 'support': 260.0}, 'accuracy': 0.9038876889848813, 'macro avg': {'precision': 0.7947103479072788, 'recall': 0.8507730962504831, 'f1-score': 0.8185716707282977, 'support': 1852.0}, 'weighted avg': {'precision': 0.9150946345921848, 'recall': 0.9038876889848813, 'f1-score': 0.9080527229470137, 'support': 1852.0}} |
95
- | No log | 41.0 | 287 | 0.7174 | {'0': {'precision': 0.955470737913486, 'recall': 0.9434673366834171, 'f1-score': 0.9494310998735778, 'support': 1592.0}, '1': {'precision': 0.6785714285714286, 'recall': 0.7307692307692307, 'f1-score': 0.7037037037037037, 'support': 260.0}, 'accuracy': 0.9136069114470843, 'macro avg': {'precision': 0.8170210832424574, 'recall': 0.8371182837263239, 'f1-score': 0.8265674017886407, 'support': 1852.0}, 'weighted avg': {'precision': 0.9165971847661131, 'recall': 0.9136069114470843, 'f1-score': 0.9149337332406581, 'support': 1852.0}} |
96
- | No log | 42.0 | 294 | 0.5540 | {'0': {'precision': 0.9675675675675676, 'recall': 0.8994974874371859, 'f1-score': 0.9322916666666666, 'support': 1592.0}, '1': {'precision': 0.5698924731182796, 'recall': 0.8153846153846154, 'f1-score': 0.6708860759493671, 'support': 260.0}, 'accuracy': 0.8876889848812095, 'macro avg': {'precision': 0.7687300203429236, 'recall': 0.8574410514109007, 'f1-score': 0.8015888713080168, 'support': 1852.0}, 'weighted avg': {'precision': 0.9117384506362421, 'recall': 0.8876889848812095, 'f1-score': 0.8955932576026828, 'support': 1852.0}} |
97
- | No log | 43.0 | 301 | 0.6035 | {'0': {'precision': 0.9635520212060967, 'recall': 0.9133165829145728, 'f1-score': 0.9377620122541116, 'support': 1592.0}, '1': {'precision': 0.597667638483965, 'recall': 0.7884615384615384, 'f1-score': 0.6799336650082919, 'support': 260.0}, 'accuracy': 0.8957883369330454, 'macro avg': {'precision': 0.7806098298450308, 'recall': 0.8508890606880557, 'f1-score': 0.8088478386312017, 'support': 1852.0}, 'weighted avg': {'precision': 0.9121859631565533, 'recall': 0.8957883369330454, 'f1-score': 0.901565807997139, 'support': 1852.0}} |
98
- | No log | 44.0 | 308 | 0.6903 | {'0': {'precision': 0.9587362991618311, 'recall': 0.9340452261306532, 'f1-score': 0.9462297168310532, 'support': 1592.0}, '1': {'precision': 0.6511627906976745, 'recall': 0.7538461538461538, 'f1-score': 0.6987522281639929, 'support': 260.0}, 'accuracy': 0.9087473002159827, 'macro avg': {'precision': 0.8049495449297528, 'recall': 0.8439456899884035, 'f1-score': 0.822490972497523, 'support': 1852.0}, 'weighted avg': {'precision': 0.9155564329627595, 'recall': 0.9087473002159827, 'f1-score': 0.911486656866995, 'support': 1852.0}} |
99
- | No log | 45.0 | 315 | 0.7107 | {'0': {'precision': 0.9588688946015425, 'recall': 0.9371859296482412, 'f1-score': 0.9479034307496823, 'support': 1592.0}, '1': {'precision': 0.6621621621621622, 'recall': 0.7538461538461538, 'f1-score': 0.7050359712230215, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8105155283818524, 'recall': 0.8455160417471975, 'f1-score': 0.826469700986352, 'support': 1852.0}, 'weighted avg': {'precision': 0.9172146017104847, 'recall': 0.9114470842332614, 'f1-score': 0.9138075671012311, 'support': 1852.0}} |
100
- | No log | 46.0 | 322 | 0.6314 | {'0': {'precision': 0.9625246548323472, 'recall': 0.9195979899497487, 'f1-score': 0.9405717956954706, 'support': 1592.0}, '1': {'precision': 0.6132930513595166, 'recall': 0.7807692307692308, 'f1-score': 0.6869712351945855, 'support': 260.0}, 'accuracy': 0.9001079913606912, 'macro avg': {'precision': 0.787908853095932, 'recall': 0.8501836103594897, 'f1-score': 0.813771515445028, 'support': 1852.0}, 'weighted avg': {'precision': 0.9134964599603516, 'recall': 0.9001079913606912, 'f1-score': 0.9049691252147847, 'support': 1852.0}} |
101
- | No log | 47.0 | 329 | 0.6935 | {'0': {'precision': 0.9592760180995475, 'recall': 0.9321608040201005, 'f1-score': 0.9455240522459382, 'support': 1592.0}, '1': {'precision': 0.6459016393442623, 'recall': 0.7576923076923077, 'f1-score': 0.6973451327433628, 'support': 260.0}, 'accuracy': 0.9076673866090713, 'macro avg': {'precision': 0.802588828721905, 'recall': 0.844926555856204, 'f1-score': 0.8214345924946505, 'support': 1852.0}, 'weighted avg': {'precision': 0.9152817748617647, 'recall': 0.9076673866090713, 'f1-score': 0.9106825192704147, 'support': 1852.0}} |
102
- | No log | 48.0 | 336 | 0.6577 | {'0': {'precision': 0.9633507853403142, 'recall': 0.9246231155778895, 'f1-score': 0.9435897435897436, 'support': 1592.0}, '1': {'precision': 0.6296296296296297, 'recall': 0.7846153846153846, 'f1-score': 0.6986301369863014, 'support': 260.0}, 'accuracy': 0.9049676025917927, 'macro avg': {'precision': 0.7964902074849719, 'recall': 0.854619250096637, 'f1-score': 0.8211099402880224, 'support': 1852.0}, 'weighted avg': {'precision': 0.9165000831347104, 'recall': 0.9049676025917927, 'f1-score': 0.9092001659888282, 'support': 1852.0}} |
103
- | No log | 49.0 | 343 | 0.7270 | {'0': {'precision': 0.9582530507385999, 'recall': 0.9371859296482412, 'f1-score': 0.947602413464592, 'support': 1592.0}, '1': {'precision': 0.6610169491525424, 'recall': 0.75, 'f1-score': 0.7027027027027027, 'support': 260.0}, 'accuracy': 0.9109071274298056, 'macro avg': {'precision': 0.8096349999455712, 'recall': 0.8435929648241206, 'f1-score': 0.8251525580836474, 'support': 1852.0}, 'weighted avg': {'precision': 0.9165244403647473, 'recall': 0.9109071274298056, 'f1-score': 0.9132212445671346, 'support': 1852.0}} |
104
- | No log | 50.0 | 350 | 0.6929 | {'0': {'precision': 0.9591968911917098, 'recall': 0.9302763819095478, 'f1-score': 0.9445153061224489, 'support': 1592.0}, '1': {'precision': 0.6396103896103896, 'recall': 0.7576923076923077, 'f1-score': 0.6936619718309859, 'support': 260.0}, 'accuracy': 0.906047516198704, 'macro avg': {'precision': 0.7994036404010497, 'recall': 0.8439843448009277, 'f1-score': 0.8190886389767174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9143305356781336, 'recall': 0.906047516198704, 'f1-score': 0.9092983153471896, 'support': 1852.0}} |
105
 
106
 
107
  ### Framework versions
 
16
 
17
  This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 0.9073
20
+ - Classification Report: {'0': {'precision': 0.9506866416978776, 'recall': 0.9566582914572864, 'f1-score': 0.9536631183469004, 'support': 1592.0}, '1': {'precision': 0.724, 'recall': 0.6961538461538461, 'f1-score': 0.7098039215686275, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8373433208489388, 'recall': 0.8264060688055663, 'f1-score': 0.831733519957764, 'support': 1852.0}, 'weighted avg': {'precision': 0.91886238314418, 'recall': 0.9200863930885529, 'f1-score': 0.9194280259266244, 'support': 1852.0}}
21
 
22
  ## Model description
23
 
 
36
  ### Training hyperparameters
37
 
38
  The following hyperparameters were used during training:
39
+ - learning_rate: 5e-06
40
  - train_batch_size: 256
41
  - eval_batch_size: 256
42
  - seed: 42
43
  - distributed_type: multi-GPU
44
+ - num_devices: 3
45
+ - total_train_batch_size: 768
46
+ - total_eval_batch_size: 768
47
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
48
  - lr_scheduler_type: linear
49
  - num_epochs: 50
 
52
 
53
  | Training Loss | Epoch | Step | Validation Loss | Classification Report |
54
  |:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
55
+ | No log | 1.0 | 9 | 0.4858 | {'0': {'precision': 0.9859307359307359, 'recall': 0.5722361809045227, 'f1-score': 0.7241653418124007, 'support': 1592.0}, '1': {'precision': 0.2661637931034483, 'recall': 0.95, 'f1-score': 0.4158249158249158, 'support': 260.0}, 'accuracy': 0.6252699784017278, 'macro avg': {'precision': 0.626047264517092, 'recall': 0.7611180904522613, 'f1-score': 0.5699951288186582, 'support': 1852.0}, 'weighted avg': {'precision': 0.8848835409333844, 'recall': 0.6252699784017278, 'f1-score': 0.6808778090063822, 'support': 1852.0}} |
56
+ | No log | 2.0 | 18 | 0.4306 | {'0': {'precision': 0.9797421731123389, 'recall': 0.6683417085427136, 'f1-score': 0.79462285287528, 'support': 1592.0}, '1': {'precision': 0.31070496083550914, 'recall': 0.9153846153846154, 'f1-score': 0.46393762183235865, 'support': 260.0}, 'accuracy': 0.703023758099352, 'macro avg': {'precision': 0.645223566973924, 'recall': 0.7918631619636645, 'f1-score': 0.6292802373538193, 'support': 1852.0}, 'weighted avg': {'precision': 0.8858168625335183, 'recall': 0.703023758099352, 'f1-score': 0.7481983603962522, 'support': 1852.0}} |
57
+ | No log | 3.0 | 27 | 0.3970 | {'0': {'precision': 0.9707016191210486, 'recall': 0.7908291457286433, 'f1-score': 0.8715818622360678, 'support': 1592.0}, '1': {'precision': 0.4, 'recall': 0.8538461538461538, 'f1-score': 0.5447852760736196, 'support': 260.0}, 'accuracy': 0.7996760259179265, 'macro avg': {'precision': 0.6853508095605243, 'recall': 0.8223376497873985, 'f1-score': 0.7081835691548437, 'support': 1852.0}, 'weighted avg': {'precision': 0.8905815214042707, 'recall': 0.7996760259179265, 'f1-score': 0.825703291824493, 'support': 1852.0}} |
58
+ | No log | 4.0 | 36 | 0.4288 | {'0': {'precision': 0.9431891542930924, 'recall': 0.917713567839196, 'f1-score': 0.9302769818529131, 'support': 1592.0}, '1': {'precision': 0.5676567656765676, 'recall': 0.6615384615384615, 'f1-score': 0.61101243339254, 'support': 260.0}, 'accuracy': 0.8817494600431965, 'macro avg': {'precision': 0.75542295998483, 'recall': 0.7896260146888288, 'f1-score': 0.7706447076227265, 'support': 1852.0}, 'weighted avg': {'precision': 0.8904686245737099, 'recall': 0.8817494600431965, 'f1-score': 0.8854558249416297, 'support': 1852.0}} |
59
+ | No log | 5.0 | 45 | 0.3387 | {'0': {'precision': 0.9824293353705118, 'recall': 0.8077889447236181, 'f1-score': 0.8865908307480179, 'support': 1592.0}, '1': {'precision': 0.43646408839779005, 'recall': 0.9115384615384615, 'f1-score': 0.5902864259028643, 'support': 260.0}, 'accuracy': 0.822354211663067, 'macro avg': {'precision': 0.709446711884151, 'recall': 0.8596637031310398, 'f1-score': 0.7384386283254412, 'support': 1852.0}, 'weighted avg': {'precision': 0.9057819464866524, 'recall': 0.822354211663067, 'f1-score': 0.8449930201326077, 'support': 1852.0}} |
60
+ | No log | 6.0 | 54 | 0.3188 | {'0': {'precision': 0.9801178203240059, 'recall': 0.8360552763819096, 'f1-score': 0.9023728813559322, 'support': 1592.0}, '1': {'precision': 0.4716599190283401, 'recall': 0.8961538461538462, 'f1-score': 0.6180371352785146, 'support': 260.0}, 'accuracy': 0.8444924406047516, 'macro avg': {'precision': 0.7258888696761729, 'recall': 0.8661045612678779, 'f1-score': 0.7602050083172234, 'support': 1852.0}, 'weighted avg': {'precision': 0.9087360415243984, 'recall': 0.8444924406047516, 'f1-score': 0.8624553360102903, 'support': 1852.0}} |
61
+ | No log | 7.0 | 63 | 0.3201 | {'0': {'precision': 0.9748778785764132, 'recall': 0.8775125628140703, 'f1-score': 0.9236363636363636, 'support': 1592.0}, '1': {'precision': 0.5346062052505967, 'recall': 0.8615384615384616, 'f1-score': 0.6597938144329897, 'support': 260.0}, 'accuracy': 0.8752699784017278, 'macro avg': {'precision': 0.7547420419135049, 'recall': 0.869525512176266, 'f1-score': 0.7917150890346767, 'support': 1852.0}, 'weighted avg': {'precision': 0.9130686803773245, 'recall': 0.8752699784017278, 'f1-score': 0.8865958329706631, 'support': 1852.0}} |
62
+ | No log | 8.0 | 72 | 0.5406 | {'0': {'precision': 0.9192692987625221, 'recall': 0.9798994974874372, 'f1-score': 0.9486166007905138, 'support': 1592.0}, '1': {'precision': 0.7935483870967742, 'recall': 0.47307692307692306, 'f1-score': 0.5927710843373494, 'support': 260.0}, 'accuracy': 0.9087473002159827, 'macro avg': {'precision': 0.8564088429296481, 'recall': 0.7264882102821801, 'f1-score': 0.7706938425639316, 'support': 1852.0}, 'weighted avg': {'precision': 0.9016194947489721, 'recall': 0.9087473002159827, 'f1-score': 0.8986598868176074, 'support': 1852.0}} |
63
+ | No log | 9.0 | 81 | 0.3013 | {'0': {'precision': 0.9760056457304164, 'recall': 0.8687185929648241, 'f1-score': 0.9192422731804586, 'support': 1592.0}, '1': {'precision': 0.5195402298850574, 'recall': 0.8692307692307693, 'f1-score': 0.6503597122302158, 'support': 260.0}, 'accuracy': 0.8687904967602592, 'macro avg': {'precision': 0.7477729378077369, 'recall': 0.8689746810977967, 'f1-score': 0.7848009927053372, 'support': 1852.0}, 'weighted avg': {'precision': 0.9119230279551499, 'recall': 0.8687904967602592, 'f1-score': 0.8814941814703814, 'support': 1852.0}} |
64
+ | No log | 10.0 | 90 | 0.5003 | {'0': {'precision': 0.9357964869775893, 'recall': 0.9704773869346733, 'f1-score': 0.9528214616096207, 'support': 1592.0}, '1': {'precision': 0.7661691542288557, 'recall': 0.5923076923076923, 'f1-score': 0.6681127982646421, 'support': 260.0}, 'accuracy': 0.9173866090712743, 'macro avg': {'precision': 0.8509828206032225, 'recall': 0.7813925396211828, 'f1-score': 0.8104671299371313, 'support': 1852.0}, 'weighted avg': {'precision': 0.9119827145614603, 'recall': 0.9173866090712743, 'f1-score': 0.9128515628678849, 'support': 1852.0}} |
65
+ | No log | 11.0 | 99 | 0.3786 | {'0': {'precision': 0.9515418502202643, 'recall': 0.949748743718593, 'f1-score': 0.9506444514303678, 'support': 1592.0}, '1': {'precision': 0.6958174904942965, 'recall': 0.7038461538461539, 'f1-score': 0.6998087954110899, 'support': 260.0}, 'accuracy': 0.9152267818574514, 'macro avg': {'precision': 0.8236796703572804, 'recall': 0.8267974487823735, 'f1-score': 0.8252266234207288, 'support': 1852.0}, 'weighted avg': {'precision': 0.9156410221809815, 'recall': 0.9152267818574514, 'f1-score': 0.9154299424859768, 'support': 1852.0}} |
66
+ | No log | 12.0 | 108 | 0.3033 | {'0': {'precision': 0.9724896836313618, 'recall': 0.8881909547738693, 'f1-score': 0.9284307288246881, 'support': 1592.0}, '1': {'precision': 0.5527638190954773, 'recall': 0.8461538461538461, 'f1-score': 0.668693009118541, 'support': 260.0}, 'accuracy': 0.8822894168466523, 'macro avg': {'precision': 0.7626267513634195, 'recall': 0.8671724004638577, 'f1-score': 0.7985618689716145, 'support': 1852.0}, 'weighted avg': {'precision': 0.9135648862343154, 'recall': 0.8822894168466523, 'f1-score': 0.8919664701186415, 'support': 1852.0}} |
67
+ | No log | 13.0 | 117 | 0.2893 | {'0': {'precision': 0.9823399558498896, 'recall': 0.8385678391959799, 'f1-score': 0.904778041341918, 'support': 1592.0}, '1': {'precision': 0.4787018255578093, 'recall': 0.9076923076923077, 'f1-score': 0.6268260292164675, 'support': 260.0}, 'accuracy': 0.8482721382289417, 'macro avg': {'precision': 0.7305208907038495, 'recall': 0.8731300734441438, 'f1-score': 0.7658020352791928, 'support': 1852.0}, 'weighted avg': {'precision': 0.9116348187678481, 'recall': 0.8482721382289417, 'f1-score': 0.8657567005467682, 'support': 1852.0}} |
68
+ | No log | 14.0 | 126 | 0.2962 | {'0': {'precision': 0.9817117776152158, 'recall': 0.842964824120603, 'f1-score': 0.9070631970260223, 'support': 1592.0}, '1': {'precision': 0.4845360824742268, 'recall': 0.9038461538461539, 'f1-score': 0.6308724832214765, 'support': 260.0}, 'accuracy': 0.8515118790496761, 'macro avg': {'precision': 0.7331239300447213, 'recall': 0.8734054889833784, 'f1-score': 0.7689678401237494, 'support': 1852.0}, 'weighted avg': {'precision': 0.9119138938481224, 'recall': 0.8515118790496761, 'f1-score': 0.8682891227338074, 'support': 1852.0}} |
69
+ | No log | 15.0 | 135 | 0.2999 | {'0': {'precision': 0.9724517906336089, 'recall': 0.8869346733668342, 'f1-score': 0.9277266754270697, 'support': 1592.0}, '1': {'precision': 0.55, 'recall': 0.8461538461538461, 'f1-score': 0.6666666666666666, 'support': 260.0}, 'accuracy': 0.8812095032397408, 'macro avg': {'precision': 0.7612258953168045, 'recall': 0.8665442597603401, 'f1-score': 0.7971966710468681, 'support': 1852.0}, 'weighted avg': {'precision': 0.9131443038275947, 'recall': 0.8812095032397408, 'f1-score': 0.8910767821885681, 'support': 1852.0}} |
70
+ | No log | 16.0 | 144 | 0.3150 | {'0': {'precision': 0.9717241379310345, 'recall': 0.8850502512562815, 'f1-score': 0.9263642340565418, 'support': 1592.0}, '1': {'precision': 0.5447761194029851, 'recall': 0.8423076923076923, 'f1-score': 0.6616314199395771, 'support': 260.0}, 'accuracy': 0.8790496760259179, 'macro avg': {'precision': 0.7582501286670098, 'recall': 0.8636789717819868, 'f1-score': 0.7939978269980594, 'support': 1852.0}, 'weighted avg': {'precision': 0.9117854312262327, 'recall': 0.8790496760259179, 'f1-score': 0.8891987201956287, 'support': 1852.0}} |
71
+ | No log | 17.0 | 153 | 0.3029 | {'0': {'precision': 0.9771265189421015, 'recall': 0.8586683417085427, 'f1-score': 0.9140755600133734, 'support': 1592.0}, '1': {'precision': 0.5033112582781457, 'recall': 0.8769230769230769, 'f1-score': 0.6395511921458625, 'support': 260.0}, 'accuracy': 0.8612311015118791, 'macro avg': {'precision': 0.7402188886101235, 'recall': 0.8677957093158097, 'f1-score': 0.776813376079618, 'support': 1852.0}, 'weighted avg': {'precision': 0.9106081778121724, 'recall': 0.8612311015118791, 'f1-score': 0.8755354219758179, 'support': 1852.0}} |
72
+ | No log | 18.0 | 162 | 0.4483 | {'0': {'precision': 0.9490049751243781, 'recall': 0.9585427135678392, 'f1-score': 0.95375, 'support': 1592.0}, '1': {'precision': 0.7295081967213115, 'recall': 0.6846153846153846, 'f1-score': 0.7063492063492064, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8392565859228448, 'recall': 0.821579049091612, 'f1-score': 0.8300496031746032, 'support': 1852.0}, 'weighted avg': {'precision': 0.9181900926271873, 'recall': 0.9200863930885529, 'f1-score': 0.9190177071548562, 'support': 1852.0}} |
73
+ | No log | 19.0 | 171 | 0.3250 | {'0': {'precision': 0.9701492537313433, 'recall': 0.8982412060301508, 'f1-score': 0.9328114807566862, 'support': 1592.0}, '1': {'precision': 0.5714285714285714, 'recall': 0.8307692307692308, 'f1-score': 0.677115987460815, 'support': 260.0}, 'accuracy': 0.8887688984881209, 'macro avg': {'precision': 0.7707889125799574, 'recall': 0.8645052183996909, 'f1-score': 0.8049637341087506, 'support': 1852.0}, 'weighted avg': {'precision': 0.9141733480084919, 'recall': 0.8887688984881209, 'f1-score': 0.8969147052399872, 'support': 1852.0}} |
74
+ | No log | 20.0 | 180 | 0.3295 | {'0': {'precision': 0.9803063457330415, 'recall': 0.8442211055276382, 'f1-score': 0.9071886601417483, 'support': 1592.0}, '1': {'precision': 0.48440748440748443, 'recall': 0.8961538461538462, 'f1-score': 0.6288798920377868, 'support': 260.0}, 'accuracy': 0.8515118790496761, 'macro avg': {'precision': 0.732356915070263, 'recall': 0.8701874758407422, 'f1-score': 0.7680342760897676, 'support': 1852.0}, 'weighted avg': {'precision': 0.9106877150933845, 'recall': 0.8515118790496761, 'f1-score': 0.8681172348139783, 'support': 1852.0}} |
75
+ | No log | 21.0 | 189 | 0.4537 | {'0': {'precision': 0.9506558400999375, 'recall': 0.9560301507537688, 'f1-score': 0.9533354212339492, 'support': 1592.0}, '1': {'precision': 0.7211155378486056, 'recall': 0.6961538461538461, 'f1-score': 0.7084148727984344, 'support': 260.0}, 'accuracy': 0.9195464362850972, 'macro avg': {'precision': 0.8358856889742716, 'recall': 0.8260919984538075, 'f1-score': 0.8308751470161918, 'support': 1852.0}, 'weighted avg': {'precision': 0.9184309596542862, 'recall': 0.9195464362850972, 'f1-score': 0.9189513269611447, 'support': 1852.0}} |
76
+ | No log | 22.0 | 198 | 0.5067 | {'0': {'precision': 0.9474335188620903, 'recall': 0.9623115577889447, 'f1-score': 0.954814583982549, 'support': 1592.0}, '1': {'precision': 0.7446808510638298, 'recall': 0.6730769230769231, 'f1-score': 0.7070707070707071, 'support': 260.0}, 'accuracy': 0.92170626349892, 'macro avg': {'precision': 0.84605718496296, 'recall': 0.8176942404329339, 'f1-score': 0.830942645526628, 'support': 1852.0}, 'weighted avg': {'precision': 0.9189693214390083, 'recall': 0.92170626349892, 'f1-score': 0.920034126100757, 'support': 1852.0}} |
77
+ | No log | 23.0 | 207 | 0.5322 | {'0': {'precision': 0.9415347137637028, 'recall': 0.9711055276381909, 'f1-score': 0.956091527520099, 'support': 1592.0}, '1': {'precision': 0.780952380952381, 'recall': 0.6307692307692307, 'f1-score': 0.6978723404255319, 'support': 260.0}, 'accuracy': 0.9233261339092873, 'macro avg': {'precision': 0.8612435473580419, 'recall': 0.8009373792037109, 'f1-score': 0.8269819339728155, 'support': 1852.0}, 'weighted avg': {'precision': 0.918990757753474, 'recall': 0.9233261339092873, 'f1-score': 0.9198404537379242, 'support': 1852.0}} |
78
+ | No log | 24.0 | 216 | 0.3741 | {'0': {'precision': 0.9659239842726082, 'recall': 0.9258793969849246, 'f1-score': 0.9454778704297627, 'support': 1592.0}, '1': {'precision': 0.6380368098159509, 'recall': 0.8, 'f1-score': 0.7098976109215017, 'support': 260.0}, 'accuracy': 0.908207343412527, 'macro avg': {'precision': 0.8019803970442796, 'recall': 0.8629396984924623, 'f1-score': 0.8276877406756322, 'support': 1852.0}, 'weighted avg': {'precision': 0.9198923075130342, 'recall': 0.908207343412527, 'f1-score': 0.9124050478206116, 'support': 1852.0}} |
79
+ | No log | 25.0 | 225 | 0.3313 | {'0': {'precision': 0.9733424470266575, 'recall': 0.8944723618090452, 'f1-score': 0.9322422258592471, 'support': 1592.0}, '1': {'precision': 0.5681233933161953, 'recall': 0.85, 'f1-score': 0.6810477657935285, 'support': 260.0}, 'accuracy': 0.8882289416846653, 'macro avg': {'precision': 0.7707329201714264, 'recall': 0.8722361809045226, 'f1-score': 0.8066449958263878, 'support': 1852.0}, 'weighted avg': {'precision': 0.9164542429420354, 'recall': 0.8882289416846653, 'f1-score': 0.8969773448565004, 'support': 1852.0}} |
80
+ | No log | 26.0 | 234 | 0.3321 | {'0': {'precision': 0.9748953974895398, 'recall': 0.878140703517588, 'f1-score': 0.9239920687376074, 'support': 1592.0}, '1': {'precision': 0.5358851674641149, 'recall': 0.8615384615384616, 'f1-score': 0.6607669616519174, 'support': 260.0}, 'accuracy': 0.8758099352051836, 'macro avg': {'precision': 0.7553902824768273, 'recall': 0.8698395825280247, 'f1-score': 0.7923795151947624, 'support': 1852.0}, 'weighted avg': {'precision': 0.9132632917624284, 'recall': 0.8758099352051836, 'f1-score': 0.8870382200106747, 'support': 1852.0}} |
81
+ | No log | 27.0 | 243 | 0.5558 | {'0': {'precision': 0.9436274509803921, 'recall': 0.9673366834170855, 'f1-score': 0.9553349875930521, 'support': 1592.0}, '1': {'precision': 0.7636363636363637, 'recall': 0.6461538461538462, 'f1-score': 0.7, 'support': 260.0}, 'accuracy': 0.9222462203023758, 'macro avg': {'precision': 0.8536319073083779, 'recall': 0.8067452647854658, 'f1-score': 0.827667493796526, 'support': 1852.0}, 'weighted avg': {'precision': 0.9183587238154637, 'recall': 0.9222462203023758, 'f1-score': 0.9194888230281528, 'support': 1852.0}} |
82
+ | No log | 28.0 | 252 | 0.3644 | {'0': {'precision': 0.9720708446866485, 'recall': 0.8963567839195979, 'f1-score': 0.9326797385620915, 'support': 1592.0}, '1': {'precision': 0.5703125, 'recall': 0.8423076923076923, 'f1-score': 0.6801242236024845, 'support': 260.0}, 'accuracy': 0.8887688984881209, 'macro avg': {'precision': 0.7711916723433243, 'recall': 0.8693322381136451, 'f1-score': 0.806401981082288, 'support': 1852.0}, 'weighted avg': {'precision': 0.9156684852813954, 'recall': 0.8887688984881209, 'f1-score': 0.8972237807383886, 'support': 1852.0}} |
83
+ | No log | 29.0 | 261 | 0.5193 | {'0': {'precision': 0.9546884833228445, 'recall': 0.9528894472361809, 'f1-score': 0.9537881169443572, 'support': 1592.0}, '1': {'precision': 0.714828897338403, 'recall': 0.7230769230769231, 'f1-score': 0.7189292543021033, 'support': 260.0}, 'accuracy': 0.9206263498920086, 'macro avg': {'precision': 0.8347586903306238, 'recall': 0.837983185156552, 'f1-score': 0.8363586856232302, 'support': 1852.0}, 'weighted avg': {'precision': 0.9210148913379876, 'recall': 0.9206263498920086, 'f1-score': 0.920816570353112, 'support': 1852.0}} |
84
+ | No log | 30.0 | 270 | 0.4313 | {'0': {'precision': 0.9656084656084656, 'recall': 0.9170854271356784, 'f1-score': 0.9407216494845361, 'support': 1592.0}, '1': {'precision': 0.611764705882353, 'recall': 0.8, 'f1-score': 0.6933333333333334, 'support': 260.0}, 'accuracy': 0.9006479481641468, 'macro avg': {'precision': 0.7886865857454093, 'recall': 0.8585427135678392, 'f1-score': 0.8170274914089347, 'support': 1852.0}, 'weighted avg': {'precision': 0.9159327757981042, 'recall': 0.9006479481641468, 'f1-score': 0.9059911083401987, 'support': 1852.0}} |
85
+ | No log | 31.0 | 279 | 0.5175 | {'0': {'precision': 0.9576923076923077, 'recall': 0.9384422110552764, 'f1-score': 0.9479695431472082, 'support': 1592.0}, '1': {'precision': 0.6643835616438356, 'recall': 0.7461538461538462, 'f1-score': 0.7028985507246377, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8110379346680716, 'recall': 0.8422980286045613, 'f1-score': 0.8254340469359229, 'support': 1852.0}, 'weighted avg': {'precision': 0.9165150539274034, 'recall': 0.9114470842332614, 'f1-score': 0.9135643282282727, 'support': 1852.0}} |
86
+ | No log | 32.0 | 288 | 0.5112 | {'0': {'precision': 0.9575835475578406, 'recall': 0.9359296482412061, 'f1-score': 0.9466327827191868, 'support': 1592.0}, '1': {'precision': 0.6554054054054054, 'recall': 0.7461538461538462, 'f1-score': 0.697841726618705, 'support': 260.0}, 'accuracy': 0.9092872570194385, 'macro avg': {'precision': 0.806494476481623, 'recall': 0.8410417471975261, 'f1-score': 0.8222372546689459, 'support': 1852.0}, 'weighted avg': {'precision': 0.9151611301930278, 'recall': 0.9092872570194385, 'f1-score': 0.9117053126402856, 'support': 1852.0}} |
87
+ | No log | 33.0 | 297 | 0.7361 | {'0': {'precision': 0.9418604651162791, 'recall': 0.9667085427135679, 'f1-score': 0.9541227526348419, 'support': 1592.0}, '1': {'precision': 0.7568807339449541, 'recall': 0.6346153846153846, 'f1-score': 0.6903765690376569, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8493705995306167, 'recall': 0.8006619636644763, 'f1-score': 0.8222496608362494, 'support': 1852.0}, 'weighted avg': {'precision': 0.9158913883859635, 'recall': 0.9200863930885529, 'f1-score': 0.9170957506179584, 'support': 1852.0}} |
88
+ | No log | 34.0 | 306 | 0.5370 | {'0': {'precision': 0.9603638726445743, 'recall': 0.928391959798995, 'f1-score': 0.9441073139572022, 'support': 1592.0}, '1': {'precision': 0.6357827476038339, 'recall': 0.7653846153846153, 'f1-score': 0.6945898778359512, 'support': 260.0}, 'accuracy': 0.9055075593952484, 'macro avg': {'precision': 0.7980733101242041, 'recall': 0.8468882875918051, 'f1-score': 0.8193485958965767, 'support': 1852.0}, 'weighted avg': {'precision': 0.9147963280924186, 'recall': 0.9055075593952484, 'f1-score': 0.9090778682814326, 'support': 1852.0}} |
89
+ | No log | 35.0 | 315 | 0.6283 | {'0': {'precision': 0.9570164348925411, 'recall': 0.9510050251256281, 'f1-score': 0.9540012602394455, 'support': 1592.0}, '1': {'precision': 0.7111111111111111, 'recall': 0.7384615384615385, 'f1-score': 0.7245283018867924, 'support': 260.0}, 'accuracy': 0.9211663066954644, 'macro avg': {'precision': 0.8340637730018261, 'recall': 0.8447332817935833, 'f1-score': 0.839264781063119, 'support': 1852.0}, 'weighted avg': {'precision': 0.922494089221282, 'recall': 0.9211663066954644, 'f1-score': 0.9217858341208225, 'support': 1852.0}} |
90
+ | No log | 36.0 | 324 | 0.8542 | {'0': {'precision': 0.940925700365408, 'recall': 0.9704773869346733, 'f1-score': 0.9554730983302412, 'support': 1592.0}, '1': {'precision': 0.7761904761904762, 'recall': 0.6269230769230769, 'f1-score': 0.6936170212765957, 'support': 260.0}, 'accuracy': 0.9222462203023758, 'macro avg': {'precision': 0.8585580882779421, 'recall': 0.7987002319288752, 'f1-score': 0.8245450598034185, 'support': 1852.0}, 'weighted avg': {'precision': 0.9177987250492728, 'recall': 0.9222462203023758, 'f1-score': 0.9187114460440923, 'support': 1852.0}} |
91
+ | No log | 37.0 | 333 | 0.5817 | {'0': {'precision': 0.961139896373057, 'recall': 0.9321608040201005, 'f1-score': 0.9464285714285714, 'support': 1592.0}, '1': {'precision': 0.6493506493506493, 'recall': 0.7692307692307693, 'f1-score': 0.704225352112676, 'support': 260.0}, 'accuracy': 0.9092872570194385, 'macro avg': {'precision': 0.8052452728618531, 'recall': 0.8506957866254349, 'f1-score': 0.8253269617706237, 'support': 1852.0}, 'weighted avg': {'precision': 0.9173681878277945, 'recall': 0.9092872570194385, 'f1-score': 0.9124259596455623, 'support': 1852.0}} |
92
+ | No log | 38.0 | 342 | 0.7546 | {'0': {'precision': 0.9490683229813665, 'recall': 0.9597989949748744, 'f1-score': 0.9544034978138664, 'support': 1592.0}, '1': {'precision': 0.7355371900826446, 'recall': 0.6846153846153846, 'f1-score': 0.7091633466135459, 'support': 260.0}, 'accuracy': 0.9211663066954644, 'macro avg': {'precision': 0.8423027565320056, 'recall': 0.8222071897951295, 'f1-score': 0.8317834222137062, 'support': 1852.0}, 'weighted avg': {'precision': 0.9190909501122155, 'recall': 0.9211663066954644, 'f1-score': 0.9199745349023744, 'support': 1852.0}} |
93
+ | No log | 39.0 | 351 | 0.7266 | {'0': {'precision': 0.9545741324921135, 'recall': 0.9503768844221105, 'f1-score': 0.952470884482216, 'support': 1592.0}, '1': {'precision': 0.704119850187266, 'recall': 0.7230769230769231, 'f1-score': 0.713472485768501, 'support': 260.0}, 'accuracy': 0.9184665226781857, 'macro avg': {'precision': 0.8293469913396898, 'recall': 0.8367269037495169, 'f1-score': 0.8329716851253585, 'support': 1852.0}, 'weighted avg': {'precision': 0.9194131641339816, 'recall': 0.9184665226781857, 'f1-score': 0.9189181935180875, 'support': 1852.0}} |
94
+ | No log | 40.0 | 360 | 0.8533 | {'0': {'precision': 0.9451632778804683, 'recall': 0.9635678391959799, 'f1-score': 0.9542768273716952, 'support': 1592.0}, '1': {'precision': 0.7467248908296943, 'recall': 0.6576923076923077, 'f1-score': 0.6993865030674846, 'support': 260.0}, 'accuracy': 0.9206263498920086, 'macro avg': {'precision': 0.8459440843550813, 'recall': 0.8106300734441438, 'f1-score': 0.82683166521959, 'support': 1852.0}, 'weighted avg': {'precision': 0.9173047570202085, 'recall': 0.9206263498920086, 'f1-score': 0.9184930885384907, 'support': 1852.0}} |
95
+ | No log | 41.0 | 369 | 0.7207 | {'0': {'precision': 0.9553571428571429, 'recall': 0.9409547738693468, 'f1-score': 0.9481012658227848, 'support': 1592.0}, '1': {'precision': 0.6690140845070423, 'recall': 0.7307692307692307, 'f1-score': 0.6985294117647058, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8121856136820926, 'recall': 0.8358620023192888, 'f1-score': 0.8233153387937453, 'support': 1852.0}, 'weighted avg': {'precision': 0.9151577934127444, 'recall': 0.9114470842332614, 'f1-score': 0.9130641804798578, 'support': 1852.0}} |
96
+ | No log | 42.0 | 378 | 0.8507 | {'0': {'precision': 0.9478260869565217, 'recall': 0.9585427135678392, 'f1-score': 0.9531542785758901, 'support': 1592.0}, '1': {'precision': 0.7272727272727273, 'recall': 0.676923076923077, 'f1-score': 0.701195219123506, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8375494071146246, 'recall': 0.8177328952454581, 'f1-score': 0.8271747488496981, 'support': 1852.0}, 'weighted avg': {'precision': 0.9168628723140884, 'recall': 0.9190064794816415, 'f1-score': 0.917782056406549, 'support': 1852.0}} |
97
+ | No log | 43.0 | 387 | 0.8223 | {'0': {'precision': 0.9534591194968554, 'recall': 0.9522613065326633, 'f1-score': 0.9528598365807668, 'support': 1592.0}, '1': {'precision': 0.7099236641221374, 'recall': 0.7153846153846154, 'f1-score': 0.7126436781609196, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8316913918094964, 'recall': 0.8338229609586394, 'f1-score': 0.8327517573708432, 'support': 1852.0}, 'weighted avg': {'precision': 0.919269476733666, 'recall': 0.9190064794816415, 'f1-score': 0.9191361858306802, 'support': 1852.0}} |
98
+ | No log | 44.0 | 396 | 0.8322 | {'0': {'precision': 0.9528301886792453, 'recall': 0.9516331658291457, 'f1-score': 0.9522313010685104, 'support': 1592.0}, '1': {'precision': 0.7061068702290076, 'recall': 0.7115384615384616, 'f1-score': 0.7088122605363985, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8294685294541264, 'recall': 0.8315858136838037, 'f1-score': 0.8305217808024544, 'support': 1852.0}, 'weighted avg': {'precision': 0.9181930057434667, 'recall': 0.91792656587473, 'f1-score': 0.9180580016417561, 'support': 1852.0}} |
99
+ | No log | 45.0 | 405 | 0.8810 | {'0': {'precision': 0.9495327102803738, 'recall': 0.957286432160804, 'f1-score': 0.9533938066937754, 'support': 1592.0}, '1': {'precision': 0.7246963562753036, 'recall': 0.6884615384615385, 'f1-score': 0.7061143984220908, 'support': 260.0}, 'accuracy': 0.9195464362850972, 'macro avg': {'precision': 0.8371145332778387, 'recall': 0.8228739853111713, 'f1-score': 0.8297541025579331, 'support': 1852.0}, 'weighted avg': {'precision': 0.9179682113379773, 'recall': 0.9195464362850972, 'f1-score': 0.918678554992567, 'support': 1852.0}} |
100
+ | No log | 46.0 | 414 | 0.9026 | {'0': {'precision': 0.9483509645301804, 'recall': 0.957286432160804, 'f1-score': 0.9527977492966552, 'support': 1592.0}, '1': {'precision': 0.7224489795918367, 'recall': 0.6807692307692308, 'f1-score': 0.700990099009901, 'support': 260.0}, 'accuracy': 0.9184665226781857, 'macro avg': {'precision': 0.8353999720610086, 'recall': 0.8190278314650175, 'f1-score': 0.826893924153278, 'support': 1852.0}, 'weighted avg': {'precision': 0.9166368629729617, 'recall': 0.9184665226781857, 'f1-score': 0.9174467832736768, 'support': 1852.0}} |
101
+ | No log | 47.0 | 423 | 0.9279 | {'0': {'precision': 0.9461633663366337, 'recall': 0.960427135678392, 'f1-score': 0.9532418952618454, 'support': 1592.0}, '1': {'precision': 0.7330508474576272, 'recall': 0.6653846153846154, 'f1-score': 0.6975806451612904, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8396071068971305, 'recall': 0.8129058755315037, 'f1-score': 0.8254112702115679, 'support': 1852.0}, 'weighted avg': {'precision': 0.9162447621743541, 'recall': 0.9190064794816415, 'f1-score': 0.91734992710518, 'support': 1852.0}} |
102
+ | No log | 48.0 | 432 | 0.8759 | {'0': {'precision': 0.9522613065326633, 'recall': 0.9522613065326633, 'f1-score': 0.9522613065326633, 'support': 1592.0}, '1': {'precision': 0.7076923076923077, 'recall': 0.7076923076923077, 'f1-score': 0.7076923076923077, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8299768071124856, 'recall': 0.8299768071124856, 'f1-score': 0.8299768071124856, 'support': 1852.0}, 'weighted avg': {'precision': 0.91792656587473, 'recall': 0.91792656587473, 'f1-score': 0.91792656587473, 'support': 1852.0}} |
103
+ | No log | 49.0 | 441 | 0.9424 | {'0': {'precision': 0.9461633663366337, 'recall': 0.960427135678392, 'f1-score': 0.9532418952618454, 'support': 1592.0}, '1': {'precision': 0.7330508474576272, 'recall': 0.6653846153846154, 'f1-score': 0.6975806451612904, 'support': 260.0}, 'accuracy': 0.9190064794816415, 'macro avg': {'precision': 0.8396071068971305, 'recall': 0.8129058755315037, 'f1-score': 0.8254112702115679, 'support': 1852.0}, 'weighted avg': {'precision': 0.9162447621743541, 'recall': 0.9190064794816415, 'f1-score': 0.91734992710518, 'support': 1852.0}} |
104
+ | No log | 50.0 | 450 | 0.9073 | {'0': {'precision': 0.9506866416978776, 'recall': 0.9566582914572864, 'f1-score': 0.9536631183469004, 'support': 1592.0}, '1': {'precision': 0.724, 'recall': 0.6961538461538461, 'f1-score': 0.7098039215686275, 'support': 260.0}, 'accuracy': 0.9200863930885529, 'macro avg': {'precision': 0.8373433208489388, 'recall': 0.8264060688055663, 'f1-score': 0.831733519957764, 'support': 1852.0}, 'weighted avg': {'precision': 0.91886238314418, 'recall': 0.9200863930885529, 'f1-score': 0.9194280259266244, 'support': 1852.0}} |
105
 
106
 
107
  ### Framework versions
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