metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: overall_binary
results: []
overall_binary
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5586
- Classification Report: {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}}
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 6
- total_train_batch_size: 96
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 60
Training results
| Training Loss | Epoch | Step | Validation Loss | Classification Report |
|---|---|---|---|---|
| No log | 1.0 | 2 | 0.6799 | {'0': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, '1': {'precision': 0.5925925925925926, 'recall': 1.0, 'f1-score': 0.7441860465116279, 'support': 32.0}, 'accuracy': 0.5925925925925926, 'macro avg': {'precision': 0.2962962962962963, 'recall': 0.5, 'f1-score': 0.37209302325581395, 'support': 54.0}, 'weighted avg': {'precision': 0.3511659807956104, 'recall': 0.5925925925925926, 'f1-score': 0.4409991386735573, 'support': 54.0}} |
| No log | 2.0 | 4 | 0.6619 | {'0': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, '1': {'precision': 0.5925925925925926, 'recall': 1.0, 'f1-score': 0.7441860465116279, 'support': 32.0}, 'accuracy': 0.5925925925925926, 'macro avg': {'precision': 0.2962962962962963, 'recall': 0.5, 'f1-score': 0.37209302325581395, 'support': 54.0}, 'weighted avg': {'precision': 0.3511659807956104, 'recall': 0.5925925925925926, 'f1-score': 0.4409991386735573, 'support': 54.0}} |
| No log | 3.0 | 6 | 0.6500 | {'0': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, '1': {'precision': 0.5925925925925926, 'recall': 1.0, 'f1-score': 0.7441860465116279, 'support': 32.0}, 'accuracy': 0.5925925925925926, 'macro avg': {'precision': 0.2962962962962963, 'recall': 0.5, 'f1-score': 0.37209302325581395, 'support': 54.0}, 'weighted avg': {'precision': 0.3511659807956104, 'recall': 0.5925925925925926, 'f1-score': 0.4409991386735573, 'support': 54.0}} |
| No log | 4.0 | 8 | 0.6325 | {'0': {'precision': 0.7333333333333333, 'recall': 0.5, 'f1-score': 0.5945945945945946, 'support': 22.0}, '1': {'precision': 0.717948717948718, 'recall': 0.875, 'f1-score': 0.7887323943661971, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7256410256410256, 'recall': 0.6875, 'f1-score': 0.6916634944803959, 'support': 54.0}, 'weighted avg': {'precision': 0.7242165242165242, 'recall': 0.7222222222222222, 'f1-score': 0.7096392166814702, 'support': 54.0}} |
| No log | 5.0 | 10 | 0.6260 | {'0': {'precision': 0.6875, 'recall': 0.5, 'f1-score': 0.5789473684210527, 'support': 22.0}, '1': {'precision': 0.7105263157894737, 'recall': 0.84375, 'f1-score': 0.7714285714285715, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.6990131578947368, 'recall': 0.671875, 'f1-score': 0.675187969924812, 'support': 54.0}, 'weighted avg': {'precision': 0.7011452241715399, 'recall': 0.7037037037037037, 'f1-score': 0.6930103035366194, 'support': 54.0}} |
| No log | 6.0 | 12 | 0.6155 | {'0': {'precision': 0.6842105263157895, 'recall': 0.5909090909090909, 'f1-score': 0.6341463414634146, 'support': 22.0}, '1': {'precision': 0.7428571428571429, 'recall': 0.8125, 'f1-score': 0.7761194029850746, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7135338345864661, 'recall': 0.7017045454545454, 'f1-score': 0.7051328722242447, 'support': 54.0}, 'weighted avg': {'precision': 0.7189640768588137, 'recall': 0.7222222222222222, 'f1-score': 0.7182785260688428, 'support': 54.0}} |
| No log | 7.0 | 14 | 0.6029 | {'0': {'precision': 0.6875, 'recall': 0.5, 'f1-score': 0.5789473684210527, 'support': 22.0}, '1': {'precision': 0.7105263157894737, 'recall': 0.84375, 'f1-score': 0.7714285714285715, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.6990131578947368, 'recall': 0.671875, 'f1-score': 0.675187969924812, 'support': 54.0}, 'weighted avg': {'precision': 0.7011452241715399, 'recall': 0.7037037037037037, 'f1-score': 0.6930103035366194, 'support': 54.0}} |
| No log | 8.0 | 16 | 0.5934 | {'0': {'precision': 0.7058823529411765, 'recall': 0.5454545454545454, 'f1-score': 0.6153846153846154, 'support': 22.0}, '1': {'precision': 0.7297297297297297, 'recall': 0.84375, 'f1-score': 0.782608695652174, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7178060413354531, 'recall': 0.6946022727272727, 'f1-score': 0.6989966555183946, 'support': 54.0}, 'weighted avg': {'precision': 0.7200141317788378, 'recall': 0.7222222222222222, 'f1-score': 0.7144803666542798, 'support': 54.0}} |
| No log | 9.0 | 18 | 0.5833 | {'0': {'precision': 0.6666666666666666, 'recall': 0.7272727272727273, 'f1-score': 0.6956521739130435, 'support': 22.0}, '1': {'precision': 0.8, 'recall': 0.75, 'f1-score': 0.7741935483870968, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7333333333333334, 'recall': 0.7386363636363636, 'f1-score': 0.7349228611500701, 'support': 54.0}, 'weighted avg': {'precision': 0.745679012345679, 'recall': 0.7407407407407407, 'f1-score': 0.7421952106384084, 'support': 54.0}} |
| No log | 10.0 | 20 | 0.5784 | {'0': {'precision': 0.6153846153846154, 'recall': 0.7272727272727273, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.7857142857142857, 'recall': 0.6875, 'f1-score': 0.7333333333333333, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7005494505494505, 'recall': 0.7073863636363636, 'f1-score': 0.7, 'support': 54.0}, 'weighted avg': {'precision': 0.7163207163207164, 'recall': 0.7037037037037037, 'f1-score': 0.7061728395061728, 'support': 54.0}} |
| No log | 11.0 | 22 | 0.5717 | {'0': {'precision': 0.6, 'recall': 0.5454545454545454, 'f1-score': 0.5714285714285714, 'support': 22.0}, '1': {'precision': 0.7058823529411765, 'recall': 0.75, 'f1-score': 0.7272727272727273, 'support': 32.0}, 'accuracy': 0.6666666666666666, 'macro avg': {'precision': 0.6529411764705882, 'recall': 0.6477272727272727, 'f1-score': 0.6493506493506493, 'support': 54.0}, 'weighted avg': {'precision': 0.6627450980392157, 'recall': 0.6666666666666666, 'f1-score': 0.6637806637806638, 'support': 54.0}} |
| No log | 12.0 | 24 | 0.5653 | {'0': {'precision': 0.6, 'recall': 0.6818181818181818, 'f1-score': 0.6382978723404256, 'support': 22.0}, '1': {'precision': 0.7586206896551724, 'recall': 0.6875, 'f1-score': 0.7213114754098361, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6793103448275861, 'recall': 0.6846590909090908, 'f1-score': 0.6798046738751309, 'support': 54.0}, 'weighted avg': {'precision': 0.6939974457215835, 'recall': 0.6851851851851852, 'f1-score': 0.68749111860378, 'support': 54.0}} |
| No log | 13.0 | 26 | 0.5638 | {'0': {'precision': 0.6296296296296297, 'recall': 0.7727272727272727, 'f1-score': 0.6938775510204082, 'support': 22.0}, '1': {'precision': 0.8148148148148148, 'recall': 0.6875, 'f1-score': 0.7457627118644068, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7222222222222222, 'recall': 0.7301136363636364, 'f1-score': 0.7198201314424075, 'support': 54.0}, 'weighted avg': {'precision': 0.7393689986282579, 'recall': 0.7222222222222222, 'f1-score': 0.724624313002037, 'support': 54.0}} |
| No log | 14.0 | 28 | 0.5485 | {'0': {'precision': 0.6153846153846154, 'recall': 0.7272727272727273, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.7857142857142857, 'recall': 0.6875, 'f1-score': 0.7333333333333333, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7005494505494505, 'recall': 0.7073863636363636, 'f1-score': 0.7, 'support': 54.0}, 'weighted avg': {'precision': 0.7163207163207164, 'recall': 0.7037037037037037, 'f1-score': 0.7061728395061728, 'support': 54.0}} |
| No log | 15.0 | 30 | 0.5394 | {'0': {'precision': 0.64, 'recall': 0.7272727272727273, 'f1-score': 0.6808510638297872, 'support': 22.0}, '1': {'precision': 0.7931034482758621, 'recall': 0.71875, 'f1-score': 0.7540983606557377, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7165517241379311, 'recall': 0.7230113636363636, 'f1-score': 0.7174747122427625, 'support': 54.0}, 'weighted avg': {'precision': 0.730727969348659, 'recall': 0.7222222222222222, 'f1-score': 0.7242568693562764, 'support': 54.0}} |
| No log | 16.0 | 32 | 0.5380 | {'0': {'precision': 0.6153846153846154, 'recall': 0.7272727272727273, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.7857142857142857, 'recall': 0.6875, 'f1-score': 0.7333333333333333, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7005494505494505, 'recall': 0.7073863636363636, 'f1-score': 0.7, 'support': 54.0}, 'weighted avg': {'precision': 0.7163207163207164, 'recall': 0.7037037037037037, 'f1-score': 0.7061728395061728, 'support': 54.0}} |
| No log | 17.0 | 34 | 0.5302 | {'0': {'precision': 0.6521739130434783, 'recall': 0.6818181818181818, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.7741935483870968, 'recall': 0.75, 'f1-score': 0.7619047619047619, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7131837307152875, 'recall': 0.7159090909090908, 'f1-score': 0.7142857142857142, 'support': 54.0}, 'weighted avg': {'precision': 0.724481845098956, 'recall': 0.7222222222222222, 'f1-score': 0.7231040564373897, 'support': 54.0}} |
| No log | 18.0 | 36 | 0.5358 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 19.0 | 38 | 0.5292 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 20.0 | 40 | 0.5441 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 21.0 | 42 | 0.5530 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 22.0 | 44 | 0.5385 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 23.0 | 46 | 0.5267 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 24.0 | 48 | 0.5220 | {'0': {'precision': 0.6451612903225806, 'recall': 0.9090909090909091, 'f1-score': 0.7547169811320755, 'support': 22.0}, '1': {'precision': 0.9130434782608695, 'recall': 0.65625, 'f1-score': 0.7636363636363637, 'support': 32.0}, 'accuracy': 0.7592592592592593, 'macro avg': {'precision': 0.7791023842917251, 'recall': 0.7826704545454546, 'f1-score': 0.7591766723842196, 'support': 54.0}, 'weighted avg': {'precision': 0.8039062905823073, 'recall': 0.7592592592592593, 'f1-score': 0.7600025411346166, 'support': 54.0}} |
| No log | 25.0 | 50 | 0.5124 | {'0': {'precision': 0.6071428571428571, 'recall': 0.7727272727272727, 'f1-score': 0.68, 'support': 22.0}, '1': {'precision': 0.8076923076923077, 'recall': 0.65625, 'f1-score': 0.7241379310344828, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7074175824175823, 'recall': 0.7144886363636364, 'f1-score': 0.7020689655172414, 'support': 54.0}, 'weighted avg': {'precision': 0.7259869759869759, 'recall': 0.7037037037037037, 'f1-score': 0.7061558109833973, 'support': 54.0}} |
| No log | 26.0 | 52 | 0.5078 | {'0': {'precision': 0.6296296296296297, 'recall': 0.7727272727272727, 'f1-score': 0.6938775510204082, 'support': 22.0}, '1': {'precision': 0.8148148148148148, 'recall': 0.6875, 'f1-score': 0.7457627118644068, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7222222222222222, 'recall': 0.7301136363636364, 'f1-score': 0.7198201314424075, 'support': 54.0}, 'weighted avg': {'precision': 0.7393689986282579, 'recall': 0.7222222222222222, 'f1-score': 0.724624313002037, 'support': 54.0}} |
| No log | 27.0 | 54 | 0.5098 | {'0': {'precision': 0.6428571428571429, 'recall': 0.8181818181818182, 'f1-score': 0.72, 'support': 22.0}, '1': {'precision': 0.8461538461538461, 'recall': 0.6875, 'f1-score': 0.7586206896551724, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7445054945054945, 'recall': 0.7528409090909092, 'f1-score': 0.7393103448275862, 'support': 54.0}, 'weighted avg': {'precision': 0.7633292633292633, 'recall': 0.7407407407407407, 'f1-score': 0.7428863346104725, 'support': 54.0}} |
| No log | 28.0 | 56 | 0.5233 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 29.0 | 58 | 0.5305 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 30.0 | 60 | 0.5221 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 31.0 | 62 | 0.5080 | {'0': {'precision': 0.6451612903225806, 'recall': 0.9090909090909091, 'f1-score': 0.7547169811320755, 'support': 22.0}, '1': {'precision': 0.9130434782608695, 'recall': 0.65625, 'f1-score': 0.7636363636363637, 'support': 32.0}, 'accuracy': 0.7592592592592593, 'macro avg': {'precision': 0.7791023842917251, 'recall': 0.7826704545454546, 'f1-score': 0.7591766723842196, 'support': 54.0}, 'weighted avg': {'precision': 0.8039062905823073, 'recall': 0.7592592592592593, 'f1-score': 0.7600025411346166, 'support': 54.0}} |
| No log | 32.0 | 64 | 0.5104 | {'0': {'precision': 0.6451612903225806, 'recall': 0.9090909090909091, 'f1-score': 0.7547169811320755, 'support': 22.0}, '1': {'precision': 0.9130434782608695, 'recall': 0.65625, 'f1-score': 0.7636363636363637, 'support': 32.0}, 'accuracy': 0.7592592592592593, 'macro avg': {'precision': 0.7791023842917251, 'recall': 0.7826704545454546, 'f1-score': 0.7591766723842196, 'support': 54.0}, 'weighted avg': {'precision': 0.8039062905823073, 'recall': 0.7592592592592593, 'f1-score': 0.7600025411346166, 'support': 54.0}} |
| No log | 33.0 | 66 | 0.5068 | {'0': {'precision': 0.6333333333333333, 'recall': 0.8636363636363636, 'f1-score': 0.7307692307692307, 'support': 22.0}, '1': {'precision': 0.875, 'recall': 0.65625, 'f1-score': 0.75, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7541666666666667, 'recall': 0.7599431818181819, 'f1-score': 0.7403846153846154, 'support': 54.0}, 'weighted avg': {'precision': 0.7765432098765432, 'recall': 0.7407407407407407, 'f1-score': 0.7421652421652423, 'support': 54.0}} |
| No log | 34.0 | 68 | 0.5262 | {'0': {'precision': 0.6451612903225806, 'recall': 0.9090909090909091, 'f1-score': 0.7547169811320755, 'support': 22.0}, '1': {'precision': 0.9130434782608695, 'recall': 0.65625, 'f1-score': 0.7636363636363637, 'support': 32.0}, 'accuracy': 0.7592592592592593, 'macro avg': {'precision': 0.7791023842917251, 'recall': 0.7826704545454546, 'f1-score': 0.7591766723842196, 'support': 54.0}, 'weighted avg': {'precision': 0.8039062905823073, 'recall': 0.7592592592592593, 'f1-score': 0.7600025411346166, 'support': 54.0}} |
| No log | 35.0 | 70 | 0.5479 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 36.0 | 72 | 0.5378 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 37.0 | 74 | 0.5421 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 38.0 | 76 | 0.5220 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 39.0 | 78 | 0.5757 | {'0': {'precision': 0.5714285714285714, 'recall': 0.9090909090909091, 'f1-score': 0.7017543859649122, 'support': 22.0}, '1': {'precision': 0.8947368421052632, 'recall': 0.53125, 'f1-score': 0.6666666666666666, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.7330827067669172, 'recall': 0.7201704545454546, 'f1-score': 0.6842105263157894, 'support': 54.0}, 'weighted avg': {'precision': 0.7630186577554999, 'recall': 0.6851851851851852, 'f1-score': 0.6809616634178036, 'support': 54.0}} |
| No log | 40.0 | 80 | 0.5522 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 41.0 | 82 | 0.5236 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 42.0 | 84 | 0.5375 | {'0': {'precision': 0.5757575757575758, 'recall': 0.8636363636363636, 'f1-score': 0.6909090909090909, 'support': 22.0}, '1': {'precision': 0.8571428571428571, 'recall': 0.5625, 'f1-score': 0.6792452830188679, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.7164502164502164, 'recall': 0.7130681818181819, 'f1-score': 0.6850771869639793, 'support': 54.0}, 'weighted avg': {'precision': 0.7425044091710759, 'recall': 0.6851851851851852, 'f1-score': 0.6839972047519217, 'support': 54.0}} |
| No log | 43.0 | 86 | 0.5382 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 44.0 | 88 | 0.5304 | {'0': {'precision': 0.625, 'recall': 0.9090909090909091, 'f1-score': 0.7407407407407407, 'support': 22.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.625, 'f1-score': 0.7407407407407407, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7670454545454546, 'recall': 0.7670454545454546, 'f1-score': 0.7407407407407407, 'support': 54.0}, 'weighted avg': {'precision': 0.7933501683501684, 'recall': 0.7407407407407407, 'f1-score': 0.7407407407407407, 'support': 54.0}} |
| No log | 45.0 | 90 | 0.5248 | {'0': {'precision': 0.6129032258064516, 'recall': 0.8636363636363636, 'f1-score': 0.7169811320754716, 'support': 22.0}, '1': {'precision': 0.8695652173913043, 'recall': 0.625, 'f1-score': 0.7272727272727273, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.741234221598878, 'recall': 0.7443181818181819, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.7649992208196976, 'recall': 0.7222222222222222, 'f1-score': 0.7230798551553269, 'support': 54.0}} |
| No log | 46.0 | 92 | 0.5316 | {'0': {'precision': 0.6129032258064516, 'recall': 0.8636363636363636, 'f1-score': 0.7169811320754716, 'support': 22.0}, '1': {'precision': 0.8695652173913043, 'recall': 0.625, 'f1-score': 0.7272727272727273, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.741234221598878, 'recall': 0.7443181818181819, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.7649992208196976, 'recall': 0.7222222222222222, 'f1-score': 0.7230798551553269, 'support': 54.0}} |
| No log | 47.0 | 94 | 0.5448 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 48.0 | 96 | 0.5319 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 49.0 | 98 | 0.5130 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 50.0 | 100 | 0.5299 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 51.0 | 102 | 0.5167 | {'0': {'precision': 0.6451612903225806, 'recall': 0.9090909090909091, 'f1-score': 0.7547169811320755, 'support': 22.0}, '1': {'precision': 0.9130434782608695, 'recall': 0.65625, 'f1-score': 0.7636363636363637, 'support': 32.0}, 'accuracy': 0.7592592592592593, 'macro avg': {'precision': 0.7791023842917251, 'recall': 0.7826704545454546, 'f1-score': 0.7591766723842196, 'support': 54.0}, 'weighted avg': {'precision': 0.8039062905823073, 'recall': 0.7592592592592593, 'f1-score': 0.7600025411346166, 'support': 54.0}} |
| No log | 52.0 | 104 | 0.5198 | {'0': {'precision': 0.59375, 'recall': 0.8636363636363636, 'f1-score': 0.7037037037037037, 'support': 22.0}, '1': {'precision': 0.8636363636363636, 'recall': 0.59375, 'f1-score': 0.7037037037037037, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7286931818181819, 'recall': 0.7286931818181819, 'f1-score': 0.7037037037037037, 'support': 54.0}, 'weighted avg': {'precision': 0.75368265993266, 'recall': 0.7037037037037037, 'f1-score': 0.7037037037037037, 'support': 54.0}} |
| No log | 53.0 | 106 | 0.5388 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 54.0 | 108 | 0.5413 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 55.0 | 110 | 0.5347 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 56.0 | 112 | 0.5411 | {'0': {'precision': 0.59375, 'recall': 0.8636363636363636, 'f1-score': 0.7037037037037037, 'support': 22.0}, '1': {'precision': 0.8636363636363636, 'recall': 0.59375, 'f1-score': 0.7037037037037037, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7286931818181819, 'recall': 0.7286931818181819, 'f1-score': 0.7037037037037037, 'support': 54.0}, 'weighted avg': {'precision': 0.75368265993266, 'recall': 0.7037037037037037, 'f1-score': 0.7037037037037037, 'support': 54.0}} |
| No log | 57.0 | 114 | 0.5357 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 58.0 | 116 | 0.5402 | {'0': {'precision': 0.6060606060606061, 'recall': 0.9090909090909091, 'f1-score': 0.7272727272727273, 'support': 22.0}, '1': {'precision': 0.9047619047619048, 'recall': 0.59375, 'f1-score': 0.7169811320754716, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7554112554112554, 'recall': 0.7514204545454546, 'f1-score': 0.7221269296740995, 'support': 54.0}, 'weighted avg': {'precision': 0.783068783068783, 'recall': 0.7222222222222222, 'f1-score': 0.721174004192872, 'support': 54.0}} |
| No log | 59.0 | 118 | 0.5490 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
| No log | 60.0 | 120 | 0.5586 | {'0': {'precision': 0.5882352941176471, 'recall': 0.9090909090909091, 'f1-score': 0.7142857142857143, 'support': 22.0}, '1': {'precision': 0.9, 'recall': 0.5625, 'f1-score': 0.6923076923076923, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7441176470588236, 'recall': 0.7357954545454546, 'f1-score': 0.7032967032967032, 'support': 54.0}, 'weighted avg': {'precision': 0.7729847494553377, 'recall': 0.7037037037037037, 'f1-score': 0.7012617012617013, 'support': 54.0}} |
Framework versions
- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1