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harun27
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binary_paragraph

Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
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End of training

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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: answerdotai/ModernBERT-large
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: binary_paragraph
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # binary_paragraph
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+
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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: 1.2539
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+ - Classification Report: {'0': {'precision': 0.9437148217636022, 'recall': 0.9478643216080402, 'f1-score': 0.9457850203697901, 'support': 1592.0}, '1': {'precision': 0.6719367588932806, 'recall': 0.6538461538461539, 'f1-score': 0.6627680311890838, 'support': 260.0}, 'accuracy': 0.9065874730021598, 'macro avg': {'precision': 0.8078257903284414, 'recall': 0.800855237727097, 'f1-score': 0.8042765257794369, 'support': 1852.0}, 'weighted avg': {'precision': 0.9055602341036219, 'recall': 0.9065874730021598, 'f1-score': 0.9060526136813539, 'support': 1852.0}}
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-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
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+
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+ ### Training results
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+
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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 | 0.4743 | {'0': {'precision': 0.9669642857142857, 'recall': 0.6802763819095478, 'f1-score': 0.7986725663716814, 'support': 1592.0}, '1': {'precision': 0.3046448087431694, 'recall': 0.8576923076923076, 'f1-score': 0.4495967741935484, 'support': 260.0}, 'accuracy': 0.7051835853131749, 'macro avg': {'precision': 0.6358045472287276, 'recall': 0.7689843448009277, 'f1-score': 0.6241346702826149, 'support': 1852.0}, 'weighted avg': {'precision': 0.8739820697248202, 'recall': 0.7051835853131749, 'f1-score': 0.7496662456555289, 'support': 1852.0}} |
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+ | No log | 2.0 | 14 | 0.4814 | {'0': {'precision': 0.9380917698470502, 'recall': 0.8090452261306532, 'f1-score': 0.8688026981450253, 'support': 1592.0}, '1': {'precision': 0.3653444676409186, 'recall': 0.6730769230769231, 'f1-score': 0.4736129905277402, 'support': 260.0}, 'accuracy': 0.7899568034557235, 'macro avg': {'precision': 0.6517181187439844, 'recall': 0.7410610746037882, 'f1-score': 0.6712078443363827, 'support': 1852.0}, 'weighted avg': {'precision': 0.8576844812004012, 'recall': 0.7899568034557235, 'f1-score': 0.8133225016112812, 'support': 1852.0}} |
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+ | No log | 3.0 | 21 | 0.4409 | {'0': {'precision': 0.984375, 'recall': 0.6331658291457286, 'f1-score': 0.7706422018348624, 'support': 1592.0}, '1': {'precision': 0.2946859903381642, 'recall': 0.9384615384615385, 'f1-score': 0.4485294117647059, 'support': 260.0}, 'accuracy': 0.6760259179265659, 'macro avg': {'precision': 0.6395304951690821, 'recall': 0.7858136838036336, 'f1-score': 0.6095858067997841, 'support': 1852.0}, 'weighted avg': {'precision': 0.8875504090107573, 'recall': 0.6760259179265659, 'f1-score': 0.7254211837904561, 'support': 1852.0}} |
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+ | No log | 4.0 | 28 | 0.4163 | {'0': {'precision': 0.9805137289636847, 'recall': 0.6953517587939698, 'f1-score': 0.8136714443219405, 'support': 1592.0}, '1': {'precision': 0.32918395573997233, 'recall': 0.9153846153846154, 'f1-score': 0.4842319430315361, 'support': 260.0}, 'accuracy': 0.7262419006479481, 'macro avg': {'precision': 0.6548488423518285, 'recall': 0.8053681870892926, 'f1-score': 0.6489516936767383, 'support': 1852.0}, 'weighted avg': {'precision': 0.8890743439538763, 'recall': 0.7262419006479481, 'f1-score': 0.7674218383092487, 'support': 1852.0}} |
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+ | No log | 5.0 | 35 | 0.3996 | {'0': {'precision': 0.9728434504792333, 'recall': 0.7650753768844221, 'f1-score': 0.8565400843881856, 'support': 1592.0}, '1': {'precision': 0.37666666666666665, 'recall': 0.8692307692307693, 'f1-score': 0.5255813953488372, 'support': 260.0}, 'accuracy': 0.7796976241900648, 'macro avg': {'precision': 0.6747550585729499, 'recall': 0.8171530730575957, 'f1-score': 0.6910607398685114, 'support': 1852.0}, 'weighted avg': {'precision': 0.8891469257539271, 'recall': 0.7796976241900648, 'f1-score': 0.8100772014776939, 'support': 1852.0}} |
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+ | No log | 6.0 | 42 | 0.3730 | {'0': {'precision': 0.984873949579832, 'recall': 0.7361809045226131, 'f1-score': 0.8425593098490295, 'support': 1592.0}, '1': {'precision': 0.36555891238670696, 'recall': 0.9307692307692308, 'f1-score': 0.5249457700650759, 'support': 260.0}, 'accuracy': 0.7634989200863931, 'macro avg': {'precision': 0.6752164309832694, 'recall': 0.8334750676459219, 'f1-score': 0.6837525399570528, 'support': 1852.0}, 'weighted avg': {'precision': 0.8979290739479678, 'recall': 0.7634989200863931, 'f1-score': 0.7979699360132693, 'support': 1852.0}} |
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+ | No log | 7.0 | 49 | 0.3489 | {'0': {'precision': 0.9704797047970479, 'recall': 0.8260050251256281, 'f1-score': 0.8924329826942654, 'support': 1592.0}, '1': {'precision': 0.4426559356136821, 'recall': 0.8461538461538461, 'f1-score': 0.5812417437252312, 'support': 260.0}, 'accuracy': 0.8288336933045356, 'macro avg': {'precision': 0.706567820205365, 'recall': 0.8360794356397372, 'f1-score': 0.7368373632097482, 'support': 1852.0}, 'weighted avg': {'precision': 0.8963791756460354, 'recall': 0.8288336933045356, 'f1-score': 0.8487452277634074, 'support': 1852.0}} |
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+ | No log | 8.0 | 56 | 0.3306 | {'0': {'precision': 0.9788359788359788, 'recall': 0.8134422110552764, 'f1-score': 0.888507718696398, 'support': 1592.0}, '1': {'precision': 0.43856332703213613, 'recall': 0.8923076923076924, 'f1-score': 0.5880861850443599, 'support': 260.0}, 'accuracy': 0.8245140388768899, 'macro avg': {'precision': 0.7086996529340575, 'recall': 0.8528749516814844, 'f1-score': 0.738296951870379, 'support': 1852.0}, 'weighted avg': {'precision': 0.9029877663797159, 'recall': 0.8245140388768899, 'f1-score': 0.8463319094363927, 'support': 1852.0}} |
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+ | No log | 9.0 | 63 | 0.3282 | {'0': {'precision': 0.9739319333816076, 'recall': 0.8448492462311558, 'f1-score': 0.9048099562731248, 'support': 1592.0}, '1': {'precision': 0.47558386411889597, 'recall': 0.8615384615384616, 'f1-score': 0.612859097127223, 'support': 260.0}, 'accuracy': 0.8471922246220303, 'macro avg': {'precision': 0.7247578987502518, 'recall': 0.8531938538848087, 'f1-score': 0.7588345267001739, 'support': 1852.0}, 'weighted avg': {'precision': 0.903969461454877, 'recall': 0.8471922246220303, 'f1-score': 0.8638233345787757, 'support': 1852.0}} |
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+ | No log | 10.0 | 70 | 0.3514 | {'0': {'precision': 0.9638718473074301, 'recall': 0.8881909547738693, 'f1-score': 0.9244851258581236, 'support': 1592.0}, '1': {'precision': 0.5376623376623376, 'recall': 0.7961538461538461, 'f1-score': 0.641860465116279, 'support': 260.0}, 'accuracy': 0.8752699784017278, 'macro avg': {'precision': 0.7507670924848839, 'recall': 0.8421724004638578, 'f1-score': 0.7831727954872013, 'support': 1852.0}, 'weighted avg': {'precision': 0.9040368189555272, 'recall': 0.8752699784017278, 'f1-score': 0.8848077976762232, 'support': 1852.0}} |
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+ | No log | 11.0 | 77 | 0.3479 | {'0': {'precision': 0.970853573907009, 'recall': 0.8787688442211056, 'f1-score': 0.9225189581272667, 'support': 1592.0}, '1': {'precision': 0.5304136253041363, 'recall': 0.8384615384615385, 'f1-score': 0.6497764530551415, 'support': 260.0}, 'accuracy': 0.8731101511879049, 'macro avg': {'precision': 0.7506335996055726, 'recall': 0.858615191341322, 'f1-score': 0.7861477055912041, 'support': 1852.0}, 'weighted avg': {'precision': 0.9090207517489383, 'recall': 0.8731101511879049, 'f1-score': 0.8842289736139013, 'support': 1852.0}} |
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+ | No log | 12.0 | 84 | 0.3811 | {'0': {'precision': 0.9602122015915119, 'recall': 0.9095477386934674, 'f1-score': 0.9341935483870968, 'support': 1592.0}, '1': {'precision': 0.5813953488372093, 'recall': 0.7692307692307693, 'f1-score': 0.6622516556291391, 'support': 260.0}, 'accuracy': 0.8898488120950324, 'macro avg': {'precision': 0.7708037752143606, 'recall': 0.8393892539621184, 'f1-score': 0.798222602008118, 'support': 1852.0}, 'weighted avg': {'precision': 0.9070305699953355, 'recall': 0.8898488120950324, 'f1-score': 0.8960159608508824, 'support': 1852.0}} |
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+ | No log | 13.0 | 91 | 0.5717 | {'0': {'precision': 0.9400244798041616, 'recall': 0.964824120603015, 'f1-score': 0.9522628642281463, 'support': 1592.0}, '1': {'precision': 0.7431192660550459, 'recall': 0.6230769230769231, 'f1-score': 0.6778242677824268, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8415718729296038, 'recall': 0.7939505218399691, 'f1-score': 0.8150435660052866, 'support': 1852.0}, 'weighted avg': {'precision': 0.9123811992562296, 'recall': 0.9168466522678186, 'f1-score': 0.9137347675349029, 'support': 1852.0}} |
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+ | No log | 14.0 | 98 | 0.3372 | {'0': {'precision': 0.9837209302325581, 'recall': 0.7971105527638191, 'f1-score': 0.8806384455239417, 'support': 1592.0}, '1': {'precision': 0.42526690391459077, 'recall': 0.9192307692307692, 'f1-score': 0.5815085158150851, 'support': 260.0}, 'accuracy': 0.8142548596112311, 'macro avg': {'precision': 0.7044939170735744, 'recall': 0.8581706609972941, 'f1-score': 0.7310734806695134, 'support': 1852.0}, 'weighted avg': {'precision': 0.9053202569913749, 'recall': 0.8142548596112311, 'f1-score': 0.8386439629514241, 'support': 1852.0}} |
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+ | No log | 15.0 | 105 | 0.3290 | {'0': {'precision': 0.9718111346018323, 'recall': 0.8662060301507538, 'f1-score': 0.9159747592162072, 'support': 1592.0}, '1': {'precision': 0.5080831408775982, 'recall': 0.8461538461538461, 'f1-score': 0.6349206349206349, 'support': 260.0}, 'accuracy': 0.8633909287257019, 'macro avg': {'precision': 0.7399471377397153, 'recall': 0.8561799381523, 'f1-score': 0.775447697068421, 'support': 1852.0}, 'weighted avg': {'precision': 0.9067089324591212, 'recall': 0.8633909287257019, 'f1-score': 0.8765179167125091, 'support': 1852.0}} |
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+ | No log | 16.0 | 112 | 0.3588 | {'0': {'precision': 0.9868312757201646, 'recall': 0.753140703517588, 'f1-score': 0.8542928393302458, 'support': 1592.0}, '1': {'precision': 0.38304552590266877, 'recall': 0.9384615384615385, 'f1-score': 0.5440356744704571, 'support': 260.0}, 'accuracy': 0.7791576673866091, 'macro avg': {'precision': 0.6849384008114167, 'recall': 0.8458011209895633, 'f1-score': 0.6991642569003514, 'support': 1852.0}, 'weighted avg': {'precision': 0.9020665376248359, 'recall': 0.7791576673866091, 'f1-score': 0.8107362179136447, 'support': 1852.0}} |
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+ | No log | 17.0 | 119 | 0.3582 | {'0': {'precision': 0.9855421686746988, 'recall': 0.7707286432160804, 'f1-score': 0.864998237574903, 'support': 1592.0}, '1': {'precision': 0.3986820428336079, 'recall': 0.9307692307692308, 'f1-score': 0.558246828143022, 'support': 260.0}, 'accuracy': 0.7931965442764579, 'macro avg': {'precision': 0.6921121057541534, 'recall': 0.8507489369926555, 'f1-score': 0.7116225328589625, 'support': 1852.0}, 'weighted avg': {'precision': 0.9031535980922563, 'recall': 0.7931965442764579, 'f1-score': 0.8219337848468852, 'support': 1852.0}} |
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+ | No log | 18.0 | 126 | 0.3201 | {'0': {'precision': 0.9827586206896551, 'recall': 0.8234924623115578, 'f1-score': 0.8961038961038961, 'support': 1592.0}, '1': {'precision': 0.4575289575289575, 'recall': 0.9115384615384615, 'f1-score': 0.609254498714653, 'support': 260.0}, 'accuracy': 0.8358531317494601, 'macro avg': {'precision': 0.7201437891093063, 'recall': 0.8675154619250096, 'f1-score': 0.7526791974092746, 'support': 1852.0}, 'weighted avg': {'precision': 0.9090222748895571, 'recall': 0.8358531317494601, 'f1-score': 0.8558334623451471, 'support': 1852.0}} |
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+ | No log | 19.0 | 133 | 0.4531 | {'0': {'precision': 0.9483301827347196, 'recall': 0.9453517587939698, 'f1-score': 0.9468386284995282, 'support': 1592.0}, '1': {'precision': 0.6716981132075471, 'recall': 0.6846153846153846, 'f1-score': 0.6780952380952381, 'support': 260.0}, 'accuracy': 0.9087473002159827, 'macro avg': {'precision': 0.8100141479711334, 'recall': 0.8149835717046772, 'f1-score': 0.8124669332973831, 'support': 1852.0}, 'weighted avg': {'precision': 0.9094941470559589, 'recall': 0.9087473002159827, 'f1-score': 0.909110074771064, 'support': 1852.0}} |
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+ | No log | 20.0 | 140 | 0.5024 | {'0': {'precision': 0.9444787168414559, 'recall': 0.9616834170854272, 'f1-score': 0.9530034235916589, 'support': 1592.0}, '1': {'precision': 0.7359307359307359, 'recall': 0.6538461538461539, 'f1-score': 0.6924643584521385, 'support': 260.0}, 'accuracy': 0.9184665226781857, 'macro avg': {'precision': 0.8402047263860959, 'recall': 0.8077647854657906, 'f1-score': 0.8227338910218986, 'support': 1852.0}, 'weighted avg': {'precision': 0.9152009225451345, 'recall': 0.9184665226781857, 'f1-score': 0.9164266649867586, 'support': 1852.0}} |
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+ | No log | 21.0 | 147 | 0.5835 | {'0': {'precision': 0.9383770591824283, 'recall': 0.9660804020100503, 'f1-score': 0.9520272361497988, 'support': 1592.0}, '1': {'precision': 0.7464788732394366, 'recall': 0.6115384615384616, 'f1-score': 0.6723044397463002, 'support': 260.0}, 'accuracy': 0.9163066954643628, 'macro avg': {'precision': 0.8424279662109324, 'recall': 0.788809431774256, 'f1-score': 0.8121658379480494, 'support': 1852.0}, 'weighted avg': {'precision': 0.9114367091040385, 'recall': 0.9163066954643628, 'f1-score': 0.9127572971298692, 'support': 1852.0}} |
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+ | No log | 22.0 | 154 | 0.4221 | {'0': {'precision': 0.9565780946208684, 'recall': 0.9271356783919598, 'f1-score': 0.9416267942583733, 'support': 1592.0}, '1': {'precision': 0.6245954692556634, 'recall': 0.7423076923076923, 'f1-score': 0.6783831282952548, 'support': 260.0}, 'accuracy': 0.9011879049676026, 'macro avg': {'precision': 0.7905867819382659, 'recall': 0.834721685349826, 'f1-score': 0.8100049612768141, 'support': 1852.0}, 'weighted avg': {'precision': 0.9099714625501593, 'recall': 0.9011879049676026, 'f1-score': 0.9046703400734861, 'support': 1852.0}} |
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+ | No log | 23.0 | 161 | 0.4644 | {'0': {'precision': 0.9564102564102565, 'recall': 0.9371859296482412, 'f1-score': 0.9467005076142132, 'support': 1592.0}, '1': {'precision': 0.6575342465753424, 'recall': 0.7384615384615385, 'f1-score': 0.6956521739130435, 'support': 260.0}, 'accuracy': 0.9092872570194385, 'macro avg': {'precision': 0.8069722514927995, 'recall': 0.8378237340548899, 'f1-score': 0.8211763407636283, 'support': 1852.0}, 'weighted avg': {'precision': 0.9144514213362404, 'recall': 0.9092872570194385, 'f1-score': 0.9114561411118891, 'support': 1852.0}} |
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+ | No log | 24.0 | 168 | 0.4462 | {'0': {'precision': 0.9587965990843689, 'recall': 0.9208542713567839, 'f1-score': 0.9394424863825697, 'support': 1592.0}, '1': {'precision': 0.6099071207430341, 'recall': 0.7576923076923077, 'f1-score': 0.6758147512864494, 'support': 260.0}, 'accuracy': 0.8979481641468683, 'macro avg': {'precision': 0.7843518599137015, 'recall': 0.8392732895245458, 'f1-score': 0.8076286188345095, 'support': 1852.0}, 'weighted avg': {'precision': 0.9098164347383932, 'recall': 0.8979481641468683, 'f1-score': 0.9024321132049286, 'support': 1852.0}} |
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+ | No log | 25.0 | 175 | 0.5146 | {'0': {'precision': 0.9583604424202993, 'recall': 0.925251256281407, 'f1-score': 0.9415148609779482, 'support': 1592.0}, '1': {'precision': 0.6222222222222222, 'recall': 0.7538461538461538, 'f1-score': 0.6817391304347826, 'support': 260.0}, 'accuracy': 0.9011879049676026, 'macro avg': {'precision': 0.7902913323212608, 'recall': 0.8395487050637804, 'f1-score': 0.8116269957063654, 'support': 1852.0}, 'weighted avg': {'precision': 0.9111704115069624, 'recall': 0.9011879049676026, 'f1-score': 0.9050452659772877, 'support': 1852.0}} |
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+ | No log | 26.0 | 182 | 0.5104 | {'0': {'precision': 0.9596827495042961, 'recall': 0.9120603015075377, 'f1-score': 0.9352657004830918, 'support': 1592.0}, '1': {'precision': 0.5870206489675516, 'recall': 0.7653846153846153, 'f1-score': 0.664440734557596, 'support': 260.0}, 'accuracy': 0.8914686825053996, 'macro avg': {'precision': 0.7733516992359238, 'recall': 0.8387224584460765, 'f1-score': 0.7998532175203439, 'support': 1852.0}, 'weighted avg': {'precision': 0.9073651759948179, 'recall': 0.8914686825053996, 'f1-score': 0.8972449169298364, 'support': 1852.0}} |
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+ | No log | 27.0 | 189 | 0.6784 | {'0': {'precision': 0.9484924623115578, 'recall': 0.9484924623115578, 'f1-score': 0.9484924623115578, 'support': 1592.0}, '1': {'precision': 0.6846153846153846, 'recall': 0.6846153846153846, 'f1-score': 0.6846153846153846, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8165539234634712, 'recall': 0.8165539234634712, 'f1-score': 0.8165539234634712, 'support': 1852.0}, 'weighted avg': {'precision': 0.9114470842332614, 'recall': 0.9114470842332614, 'f1-score': 0.9114470842332614, 'support': 1852.0}} |
82
+ | No log | 28.0 | 196 | 0.5543 | {'0': {'precision': 0.9586070959264126, 'recall': 0.9164572864321608, 'f1-score': 0.9370584457289659, 'support': 1592.0}, '1': {'precision': 0.5969696969696969, 'recall': 0.7576923076923077, 'f1-score': 0.6677966101694915, 'support': 260.0}, 'accuracy': 0.8941684665226782, 'macro avg': {'precision': 0.7777883964480548, 'recall': 0.8370747970622343, 'f1-score': 0.8024275279492288, 'support': 1852.0}, 'weighted avg': {'precision': 0.9078372666992278, 'recall': 0.8941684665226782, 'f1-score': 0.8992571081234242, 'support': 1852.0}} |
83
+ | No log | 29.0 | 203 | 0.6011 | {'0': {'precision': 0.9577922077922078, 'recall': 0.9265075376884422, 'f1-score': 0.941890166028097, 'support': 1592.0}, '1': {'precision': 0.625, 'recall': 0.75, 'f1-score': 0.6818181818181818, 'support': 260.0}, 'accuracy': 0.9017278617710583, 'macro avg': {'precision': 0.7913961038961039, 'recall': 0.8382537688442211, 'f1-score': 0.8118541739231394, 'support': 1852.0}, 'weighted avg': {'precision': 0.9110719194412499, 'recall': 0.9017278617710583, 'f1-score': 0.90537898033988, 'support': 1852.0}} |
84
+ | No log | 30.0 | 210 | 0.9177 | {'0': {'precision': 0.9303303303303303, 'recall': 0.9729899497487438, 'f1-score': 0.9511820693890083, 'support': 1592.0}, '1': {'precision': 0.7700534759358288, 'recall': 0.5538461538461539, 'f1-score': 0.6442953020134228, 'support': 260.0}, 'accuracy': 0.9141468682505399, 'macro avg': {'precision': 0.8501919031330796, 'recall': 0.7634180517974488, 'f1-score': 0.7977386857012155, 'support': 1852.0}, 'weighted avg': {'precision': 0.907829260058964, 'recall': 0.9141468682505399, 'f1-score': 0.9080986139259131, 'support': 1852.0}} |
85
+ | No log | 31.0 | 217 | 0.7935 | {'0': {'precision': 0.9435483870967742, 'recall': 0.9554020100502513, 'f1-score': 0.949438202247191, 'support': 1592.0}, '1': {'precision': 0.7041666666666667, 'recall': 0.65, 'f1-score': 0.676, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.8238575268817205, 'recall': 0.8027010050251256, 'f1-score': 0.8127191011235955, 'support': 1852.0}, 'weighted avg': {'precision': 0.9099418820687893, 'recall': 0.9125269978401728, 'f1-score': 0.9110505496638921, 'support': 1852.0}} |
86
+ | No log | 32.0 | 224 | 0.7311 | {'0': {'precision': 0.9525336754329699, 'recall': 0.9327889447236181, 'f1-score': 0.9425579181212314, 'support': 1592.0}, '1': {'precision': 0.6348122866894198, 'recall': 0.7153846153846154, 'f1-score': 0.6726943942133815, 'support': 260.0}, 'accuracy': 0.902267818574514, 'macro avg': {'precision': 0.7936729810611949, 'recall': 0.8240867800541167, 'f1-score': 0.8076261561673064, 'support': 1852.0}, 'weighted avg': {'precision': 0.9079291608145448, 'recall': 0.902267818574514, 'f1-score': 0.9046721102292006, 'support': 1852.0}} |
87
+ | No log | 33.0 | 231 | 0.8073 | {'0': {'precision': 0.95, 'recall': 0.9428391959798995, 'f1-score': 0.9464060529634301, 'support': 1592.0}, '1': {'precision': 0.6654411764705882, 'recall': 0.6961538461538461, 'f1-score': 0.6804511278195489, 'support': 260.0}, 'accuracy': 0.908207343412527, 'macro avg': {'precision': 0.807720588235294, 'recall': 0.8194965210668728, 'f1-score': 0.8134285903914895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9100511370855037, 'recall': 0.908207343412527, 'f1-score': 0.909068968439991, 'support': 1852.0}} |
88
+ | No log | 34.0 | 238 | 0.9300 | {'0': {'precision': 0.9418316831683168, 'recall': 0.9560301507537688, 'f1-score': 0.9488778054862843, 'support': 1592.0}, '1': {'precision': 0.7033898305084746, 'recall': 0.6384615384615384, 'f1-score': 0.6693548387096774, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8226107568383957, 'recall': 0.7972458446076536, 'f1-score': 0.8091163220979809, 'support': 1852.0}, 'weighted avg': {'precision': 0.9083571250195269, 'recall': 0.9114470842332614, 'f1-score': 0.9096359203016634, 'support': 1852.0}} |
89
+ | No log | 35.0 | 245 | 1.2332 | {'0': {'precision': 0.9309723889555822, 'recall': 0.9742462311557789, 'f1-score': 0.9521178637200737, 'support': 1592.0}, '1': {'precision': 0.7795698924731183, 'recall': 0.5576923076923077, 'f1-score': 0.6502242152466368, 'support': 260.0}, 'accuracy': 0.9157667386609071, 'macro avg': {'precision': 0.8552711407143503, 'recall': 0.7659692694240433, 'f1-score': 0.8011710394833552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9097171788662515, 'recall': 0.9157667386609071, 'f1-score': 0.909735386072615, 'support': 1852.0}} |
90
+ | No log | 36.0 | 252 | 1.1424 | {'0': {'precision': 0.9333333333333333, 'recall': 0.9673366834170855, 'f1-score': 0.9500308451573103, 'support': 1592.0}, '1': {'precision': 0.7425742574257426, 'recall': 0.5769230769230769, 'f1-score': 0.6493506493506493, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.837953795379538, 'recall': 0.7721298801700811, 'f1-score': 0.7996907472539798, 'support': 1852.0}, 'weighted avg': {'precision': 0.9065529015104535, 'recall': 0.9125269978401728, 'f1-score': 0.9078187226358567, 'support': 1852.0}} |
91
+ | No log | 37.0 | 259 | 0.6708 | {'0': {'precision': 0.9605614973262032, 'recall': 0.9026381909547738, 'f1-score': 0.930699481865285, 'support': 1592.0}, '1': {'precision': 0.5646067415730337, 'recall': 0.7730769230769231, 'f1-score': 0.6525974025974026, 'support': 260.0}, 'accuracy': 0.8844492440604752, 'macro avg': {'precision': 0.7625841194496185, 'recall': 0.8378575570158484, 'f1-score': 0.7916484422313438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9049738966265143, 'recall': 0.8844492440604752, 'f1-score': 0.8916570733287572, 'support': 1852.0}} |
92
+ | No log | 38.0 | 266 | 0.8283 | {'0': {'precision': 0.9558441558441558, 'recall': 0.9246231155778895, 'f1-score': 0.9399744572158365, 'support': 1592.0}, '1': {'precision': 0.6153846153846154, 'recall': 0.7384615384615385, 'f1-score': 0.6713286713286714, 'support': 260.0}, 'accuracy': 0.8984881209503239, 'macro avg': {'precision': 0.7856143856143856, 'recall': 0.831542327019714, 'f1-score': 0.8056515642722539, 'support': 1852.0}, 'weighted avg': {'precision': 0.9080474600992959, 'recall': 0.8984881209503239, 'f1-score': 0.9022596060653705, 'support': 1852.0}} |
93
+ | No log | 39.0 | 273 | 0.9437 | {'0': {'precision': 0.9468354430379747, 'recall': 0.9396984924623115, 'f1-score': 0.9432534678436317, 'support': 1592.0}, '1': {'precision': 0.6470588235294118, 'recall': 0.676923076923077, 'f1-score': 0.6616541353383458, 'support': 260.0}, 'accuracy': 0.9028077753779697, 'macro avg': {'precision': 0.7969471332836933, 'recall': 0.8083107846926942, 'f1-score': 0.8024538015909888, 'support': 1852.0}, 'weighted avg': {'precision': 0.9047501724806172, 'recall': 0.9028077753779697, 'f1-score': 0.9037200842305786, 'support': 1852.0}} |
94
+ | No log | 40.0 | 280 | 1.1990 | {'0': {'precision': 0.9343065693430657, 'recall': 0.964824120603015, 'f1-score': 0.9493201483312732, 'support': 1592.0}, '1': {'precision': 0.7307692307692307, 'recall': 0.5846153846153846, 'f1-score': 0.6495726495726496, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8325379000561481, 'recall': 0.7747197526091998, 'f1-score': 0.7994463989519613, 'support': 1852.0}, 'weighted avg': {'precision': 0.9057322129558102, 'recall': 0.9114470842332614, 'f1-score': 0.907238966000149, 'support': 1852.0}} |
95
+ | No log | 41.0 | 287 | 1.0497 | {'0': {'precision': 0.9434431323803605, 'recall': 0.9535175879396985, 'f1-score': 0.9484536082474226, 'support': 1592.0}, '1': {'precision': 0.6954732510288066, 'recall': 0.65, 'f1-score': 0.6719681908548708, 'support': 260.0}, 'accuracy': 0.9109071274298056, 'macro avg': {'precision': 0.8194581917045836, 'recall': 0.8017587939698493, 'f1-score': 0.8102108995511468, 'support': 1852.0}, 'weighted avg': {'precision': 0.9086309460135117, 'recall': 0.9109071274298056, 'f1-score': 0.9096381608812977, 'support': 1852.0}} |
96
+ | No log | 42.0 | 294 | 0.9548 | {'0': {'precision': 0.9487017099430018, 'recall': 0.9409547738693468, 'f1-score': 0.9448123620309051, 'support': 1592.0}, '1': {'precision': 0.6556776556776557, 'recall': 0.6884615384615385, 'f1-score': 0.6716697936210131, 'support': 260.0}, 'accuracy': 0.9055075593952484, 'macro avg': {'precision': 0.8021896828103288, 'recall': 0.8147081561654426, 'f1-score': 0.8082410778259591, 'support': 1852.0}, 'weighted avg': {'precision': 0.9075644237070462, 'recall': 0.9055075593952484, 'f1-score': 0.9064662131180694, 'support': 1852.0}} |
97
+ | No log | 43.0 | 301 | 1.0401 | {'0': {'precision': 0.946608040201005, 'recall': 0.946608040201005, 'f1-score': 0.946608040201005, 'support': 1592.0}, '1': {'precision': 0.6730769230769231, 'recall': 0.6730769230769231, 'f1-score': 0.6730769230769231, 'support': 260.0}, 'accuracy': 0.908207343412527, 'macro avg': {'precision': 0.809842481638964, 'recall': 0.809842481638964, 'f1-score': 0.809842481638964, 'support': 1852.0}, 'weighted avg': {'precision': 0.908207343412527, 'recall': 0.908207343412527, 'f1-score': 0.908207343412527, 'support': 1852.0}} |
98
+ | No log | 44.0 | 308 | 1.0506 | {'0': {'precision': 0.947136563876652, 'recall': 0.9453517587939698, 'f1-score': 0.9462433197107828, 'support': 1592.0}, '1': {'precision': 0.6692015209125475, 'recall': 0.676923076923077, 'f1-score': 0.6730401529636711, 'support': 260.0}, 'accuracy': 0.9076673866090713, 'macro avg': {'precision': 0.8081690423945997, 'recall': 0.8111374178585233, 'f1-score': 0.809641736337227, 'support': 1852.0}, 'weighted avg': {'precision': 0.9081176053611729, 'recall': 0.9076673866090713, 'f1-score': 0.9078886634719874, 'support': 1852.0}} |
99
+ | No log | 45.0 | 315 | 1.1708 | {'0': {'precision': 0.9428216283405843, 'recall': 0.9528894472361809, 'f1-score': 0.9478288034989066, 'support': 1592.0}, '1': {'precision': 0.691358024691358, 'recall': 0.6461538461538462, 'f1-score': 0.6679920477137177, 'support': 260.0}, 'accuracy': 0.9098272138228942, 'macro avg': {'precision': 0.8170898265159712, 'recall': 0.7995216466950135, 'f1-score': 0.8079104256063121, 'support': 1852.0}, 'weighted avg': {'precision': 0.907518962601492, 'recall': 0.9098272138228942, 'f1-score': 0.908542865861677, 'support': 1852.0}} |
100
+ | No log | 46.0 | 322 | 1.1573 | {'0': {'precision': 0.9448275862068966, 'recall': 0.946608040201005, 'f1-score': 0.945716975211798, 'support': 1592.0}, '1': {'precision': 0.669260700389105, 'recall': 0.6615384615384615, 'f1-score': 0.6653771760154739, 'support': 260.0}, 'accuracy': 0.9065874730021598, 'macro avg': {'precision': 0.8070441432980008, 'recall': 0.8040732508697332, 'f1-score': 0.8055470756136359, 'support': 1852.0}, 'weighted avg': {'precision': 0.9061410903577466, 'recall': 0.9065874730021598, 'f1-score': 0.9063604159293767, 'support': 1852.0}} |
101
+ | No log | 47.0 | 329 | 1.2032 | {'0': {'precision': 0.9451029320024953, 'recall': 0.9516331658291457, 'f1-score': 0.9483568075117371, 'support': 1592.0}, '1': {'precision': 0.6907630522088354, 'recall': 0.6615384615384615, 'f1-score': 0.6758349705304518, 'support': 260.0}, 'accuracy': 0.9109071274298056, 'macro avg': {'precision': 0.8179329921056653, 'recall': 0.8065858136838036, 'f1-score': 0.8120958890210945, 'support': 1852.0}, 'weighted avg': {'precision': 0.909396469396474, 'recall': 0.9109071274298056, 'f1-score': 0.9100978023199799, 'support': 1852.0}} |
102
+ | No log | 48.0 | 336 | 1.2341 | {'0': {'precision': 0.944792973651192, 'recall': 0.9459798994974874, 'f1-score': 0.9453860640301318, 'support': 1592.0}, '1': {'precision': 0.6666666666666666, 'recall': 0.6615384615384615, 'f1-score': 0.6640926640926641, 'support': 260.0}, 'accuracy': 0.906047516198704, 'macro avg': {'precision': 0.8057298201589294, 'recall': 0.8037591805179745, 'f1-score': 0.804739364061398, 'support': 1852.0}, 'weighted avg': {'precision': 0.9057471638153515, 'recall': 0.906047516198704, 'f1-score': 0.9058956299136406, 'support': 1852.0}} |
103
+ | No log | 49.0 | 343 | 1.2748 | {'0': {'precision': 0.9439252336448598, 'recall': 0.9516331658291457, 'f1-score': 0.9477635283077885, 'support': 1592.0}, '1': {'precision': 0.6882591093117408, 'recall': 0.6538461538461539, 'f1-score': 0.6706114398422091, 'support': 260.0}, 'accuracy': 0.9098272138228942, 'macro avg': {'precision': 0.8160921714783003, 'recall': 0.8027396598376497, 'f1-score': 0.8091874840749989, 'support': 1852.0}, 'weighted avg': {'precision': 0.9080325812006855, 'recall': 0.9098272138228942, 'f1-score': 0.908854487810461, 'support': 1852.0}} |
104
+ | No log | 50.0 | 350 | 1.2539 | {'0': {'precision': 0.9437148217636022, 'recall': 0.9478643216080402, 'f1-score': 0.9457850203697901, 'support': 1592.0}, '1': {'precision': 0.6719367588932806, 'recall': 0.6538461538461539, 'f1-score': 0.6627680311890838, 'support': 260.0}, 'accuracy': 0.9065874730021598, 'macro avg': {'precision': 0.8078257903284414, 'recall': 0.800855237727097, 'f1-score': 0.8042765257794369, 'support': 1852.0}, 'weighted avg': {'precision': 0.9055602341036219, 'recall': 0.9065874730021598, 'f1-score': 0.9060526136813539, 'support': 1852.0}} |
105
+
106
+
107
+ ### Framework versions
108
+
109
+ - Transformers 4.52.3
110
+ - Pytorch 2.6.0+cu124
111
+ - Datasets 3.5.0
112
+ - Tokenizers 0.21.1
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