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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: overall_binary
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# overall_binary
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5527
- Classification Report: {'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}}
## 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 | 0.6891 | {'0': {'precision': 0.4375, 'recall': 0.6363636363636364, 'f1-score': 0.5185185185185185, 'support': 22.0}, '1': {'precision': 0.6363636363636364, 'recall': 0.4375, 'f1-score': 0.5185185185185185, 'support': 32.0}, 'accuracy': 0.5185185185185185, 'macro avg': {'precision': 0.5369318181818181, 'recall': 0.5369318181818181, 'f1-score': 0.5185185185185185, 'support': 54.0}, 'weighted avg': {'precision': 0.5553451178451179, 'recall': 0.5185185185185185, 'f1-score': 0.5185185185185185, 'support': 54.0}} |
| No log | 2.0 | 4 | 0.6670 | {'0': {'precision': 0.5555555555555556, 'recall': 0.22727272727272727, 'f1-score': 0.3225806451612903, 'support': 22.0}, '1': {'precision': 0.6222222222222222, 'recall': 0.875, 'f1-score': 0.7272727272727273, 'support': 32.0}, 'accuracy': 0.6111111111111112, 'macro avg': {'precision': 0.5888888888888889, 'recall': 0.5511363636363636, 'f1-score': 0.5249266862170088, 'support': 54.0}, 'weighted avg': {'precision': 0.5950617283950618, 'recall': 0.6111111111111112, 'f1-score': 0.5623981753014011, 'support': 54.0}} |
| No log | 3.0 | 6 | 0.6707 | {'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 | 0.6573 | {'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 | 5.0 | 10 | 0.6460 | {'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 | 6.0 | 12 | 0.6352 | {'0': {'precision': 0.5, 'recall': 0.13636363636363635, 'f1-score': 0.21428571428571427, 'support': 22.0}, '1': {'precision': 0.6041666666666666, 'recall': 0.90625, 'f1-score': 0.725, 'support': 32.0}, 'accuracy': 0.5925925925925926, 'macro avg': {'precision': 0.5520833333333333, 'recall': 0.5213068181818181, 'f1-score': 0.46964285714285714, 'support': 54.0}, 'weighted avg': {'precision': 0.5617283950617283, 'recall': 0.5925925925925926, 'f1-score': 0.5169312169312169, 'support': 54.0}} |
| No log | 7.0 | 14 | 0.6288 | {'0': {'precision': 0.625, 'recall': 0.22727272727272727, 'f1-score': 0.3333333333333333, 'support': 22.0}, '1': {'precision': 0.6304347826086957, 'recall': 0.90625, 'f1-score': 0.7435897435897436, 'support': 32.0}, 'accuracy': 0.6296296296296297, 'macro avg': {'precision': 0.6277173913043479, 'recall': 0.5667613636363636, 'f1-score': 0.5384615384615384, 'support': 54.0}, 'weighted avg': {'precision': 0.6282206119162642, 'recall': 0.6296296296296297, 'f1-score': 0.5764482431149097, 'support': 54.0}} |
| No log | 8.0 | 16 | 0.6234 | {'0': {'precision': 0.6666666666666666, 'recall': 0.45454545454545453, 'f1-score': 0.5405405405405406, 'support': 22.0}, '1': {'precision': 0.6923076923076923, 'recall': 0.84375, 'f1-score': 0.7605633802816901, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6794871794871795, 'recall': 0.6491477272727273, 'f1-score': 0.6505519604111154, 'support': 54.0}, 'weighted avg': {'precision': 0.6818613485280152, 'recall': 0.6851851851851852, 'f1-score': 0.6709244455723329, 'support': 54.0}} |
| No log | 9.0 | 18 | 0.6166 | {'0': {'precision': 0.6470588235294118, 'recall': 0.5, 'f1-score': 0.5641025641025641, 'support': 22.0}, '1': {'precision': 0.7027027027027027, 'recall': 0.8125, 'f1-score': 0.7536231884057971, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6748807631160573, 'recall': 0.65625, 'f1-score': 0.6588628762541806, 'support': 54.0}, 'weighted avg': {'precision': 0.6800329741506212, 'recall': 0.6851851851851852, 'f1-score': 0.6764110822081837, 'support': 54.0}} |
| No log | 10.0 | 20 | 0.6029 | {'0': {'precision': 0.6666666666666666, 'recall': 0.45454545454545453, 'f1-score': 0.5405405405405406, 'support': 22.0}, '1': {'precision': 0.6923076923076923, 'recall': 0.84375, 'f1-score': 0.7605633802816901, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6794871794871795, 'recall': 0.6491477272727273, 'f1-score': 0.6505519604111154, 'support': 54.0}, 'weighted avg': {'precision': 0.6818613485280152, 'recall': 0.6851851851851852, 'f1-score': 0.6709244455723329, 'support': 54.0}} |
| No log | 11.0 | 22 | 0.5977 | {'0': {'precision': 0.75, 'recall': 0.4090909090909091, 'f1-score': 0.5294117647058824, 'support': 22.0}, '1': {'precision': 0.6904761904761905, 'recall': 0.90625, 'f1-score': 0.7837837837837838, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.7202380952380952, 'recall': 0.6576704545454546, 'f1-score': 0.656597774244833, 'support': 54.0}, 'weighted avg': {'precision': 0.7147266313932981, 'recall': 0.7037037037037037, 'f1-score': 0.6801507389742684, 'support': 54.0}} |
| No log | 12.0 | 24 | 0.5902 | {'0': {'precision': 0.6666666666666666, 'recall': 0.5454545454545454, 'f1-score': 0.6, 'support': 22.0}, '1': {'precision': 0.7222222222222222, 'recall': 0.8125, 'f1-score': 0.7647058823529411, 'support': 32.0}, 'accuracy': 0.7037037037037037, 'macro avg': {'precision': 0.6944444444444444, 'recall': 0.6789772727272727, 'f1-score': 0.6823529411764706, 'support': 54.0}, 'weighted avg': {'precision': 0.6995884773662552, 'recall': 0.7037037037037037, 'f1-score': 0.69760348583878, 'support': 54.0}} |
| No log | 13.0 | 26 | 0.5839 | {'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 | 14.0 | 28 | 0.5809 | {'0': {'precision': 0.5925925925925926, 'recall': 0.7272727272727273, 'f1-score': 0.6530612244897959, 'support': 22.0}, '1': {'precision': 0.7777777777777778, 'recall': 0.65625, 'f1-score': 0.711864406779661, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6851851851851851, 'recall': 0.6917613636363636, 'f1-score': 0.6824628156347284, 'support': 54.0}, 'weighted avg': {'precision': 0.7023319615912208, 'recall': 0.6851851851851852, 'f1-score': 0.6879075547356419, 'support': 54.0}} |
| No log | 15.0 | 30 | 0.5742 | {'0': {'precision': 0.5925925925925926, 'recall': 0.7272727272727273, 'f1-score': 0.6530612244897959, 'support': 22.0}, '1': {'precision': 0.7777777777777778, 'recall': 0.65625, 'f1-score': 0.711864406779661, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6851851851851851, 'recall': 0.6917613636363636, 'f1-score': 0.6824628156347284, 'support': 54.0}, 'weighted avg': {'precision': 0.7023319615912208, 'recall': 0.6851851851851852, 'f1-score': 0.6879075547356419, 'support': 54.0}} |
| No log | 16.0 | 32 | 0.5630 | {'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 | 17.0 | 34 | 0.5591 | {'0': {'precision': 0.7, 'recall': 0.6363636363636364, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.7647058823529411, 'recall': 0.8125, 'f1-score': 0.7878787878787878, 'support': 32.0}, 'accuracy': 0.7407407407407407, 'macro avg': {'precision': 0.7323529411764705, 'recall': 0.7244318181818181, 'f1-score': 0.7272727272727273, 'support': 54.0}, 'weighted avg': {'precision': 0.7383442265795206, 'recall': 0.7407407407407407, 'f1-score': 0.7384960718294051, 'support': 54.0}} |
| No log | 18.0 | 36 | 0.5496 | {'0': {'precision': 0.6086956521739131, 'recall': 0.6363636363636364, 'f1-score': 0.6222222222222222, 'support': 22.0}, '1': {'precision': 0.7419354838709677, 'recall': 0.71875, 'f1-score': 0.7301587301587301, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6753155680224404, 'recall': 0.6775568181818181, 'f1-score': 0.6761904761904762, 'support': 54.0}, 'weighted avg': {'precision': 0.6876525894758714, 'recall': 0.6851851851851852, 'f1-score': 0.6861845972957084, 'support': 54.0}} |
| No log | 19.0 | 38 | 0.5427 | {'0': {'precision': 0.5833333333333334, 'recall': 0.6363636363636364, 'f1-score': 0.6086956521739131, 'support': 22.0}, '1': {'precision': 0.7333333333333333, 'recall': 0.6875, 'f1-score': 0.7096774193548387, 'support': 32.0}, 'accuracy': 0.6666666666666666, 'macro avg': {'precision': 0.6583333333333333, 'recall': 0.6619318181818181, 'f1-score': 0.6591865357643759, 'support': 54.0}, 'weighted avg': {'precision': 0.6722222222222222, 'recall': 0.6666666666666666, 'f1-score': 0.6685366993922394, 'support': 54.0}} |
| No log | 20.0 | 40 | 0.5372 | {'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 | 21.0 | 42 | 0.5395 | {'0': {'precision': 0.5925925925925926, 'recall': 0.7272727272727273, 'f1-score': 0.6530612244897959, 'support': 22.0}, '1': {'precision': 0.7777777777777778, 'recall': 0.65625, 'f1-score': 0.711864406779661, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6851851851851851, 'recall': 0.6917613636363636, 'f1-score': 0.6824628156347284, 'support': 54.0}, 'weighted avg': {'precision': 0.7023319615912208, 'recall': 0.6851851851851852, 'f1-score': 0.6879075547356419, 'support': 54.0}} |
| No log | 22.0 | 44 | 0.5482 | {'0': {'precision': 0.5862068965517241, 'recall': 0.7727272727272727, 'f1-score': 0.6666666666666666, 'support': 22.0}, '1': {'precision': 0.8, 'recall': 0.625, 'f1-score': 0.7017543859649122, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.693103448275862, 'recall': 0.6988636363636364, 'f1-score': 0.6842105263157894, 'support': 54.0}, 'weighted avg': {'precision': 0.7128991060025542, 'recall': 0.6851851851851852, 'f1-score': 0.6874593892137751, 'support': 54.0}} |
| No log | 23.0 | 46 | 0.5480 | {'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 | 24.0 | 48 | 0.5387 | {'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 | 25.0 | 50 | 0.5280 | {'0': {'precision': 0.5769230769230769, 'recall': 0.6818181818181818, 'f1-score': 0.625, 'support': 22.0}, '1': {'precision': 0.75, 'recall': 0.65625, 'f1-score': 0.7, 'support': 32.0}, 'accuracy': 0.6666666666666666, 'macro avg': {'precision': 0.6634615384615384, 'recall': 0.6690340909090908, 'f1-score': 0.6625, 'support': 54.0}, 'weighted avg': {'precision': 0.6794871794871795, 'recall': 0.6666666666666666, 'f1-score': 0.6694444444444444, 'support': 54.0}} |
| No log | 26.0 | 52 | 0.5293 | {'0': {'precision': 0.5769230769230769, 'recall': 0.6818181818181818, 'f1-score': 0.625, 'support': 22.0}, '1': {'precision': 0.75, 'recall': 0.65625, 'f1-score': 0.7, 'support': 32.0}, 'accuracy': 0.6666666666666666, 'macro avg': {'precision': 0.6634615384615384, 'recall': 0.6690340909090908, 'f1-score': 0.6625, 'support': 54.0}, 'weighted avg': {'precision': 0.6794871794871795, 'recall': 0.6666666666666666, 'f1-score': 0.6694444444444444, 'support': 54.0}} |
| No log | 27.0 | 54 | 0.5337 | {'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 | 28.0 | 56 | 0.5526 | {'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 | 29.0 | 58 | 0.5693 | {'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 | 30.0 | 60 | 0.5618 | {'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 | 31.0 | 62 | 0.5456 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 32.0 | 64 | 0.5323 | {'0': {'precision': 0.5925925925925926, 'recall': 0.7272727272727273, 'f1-score': 0.6530612244897959, 'support': 22.0}, '1': {'precision': 0.7777777777777778, 'recall': 0.65625, 'f1-score': 0.711864406779661, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6851851851851851, 'recall': 0.6917613636363636, 'f1-score': 0.6824628156347284, 'support': 54.0}, 'weighted avg': {'precision': 0.7023319615912208, 'recall': 0.6851851851851852, 'f1-score': 0.6879075547356419, 'support': 54.0}} |
| No log | 33.0 | 66 | 0.5386 | {'0': {'precision': 0.5925925925925926, 'recall': 0.7272727272727273, 'f1-score': 0.6530612244897959, 'support': 22.0}, '1': {'precision': 0.7777777777777778, 'recall': 0.65625, 'f1-score': 0.711864406779661, 'support': 32.0}, 'accuracy': 0.6851851851851852, 'macro avg': {'precision': 0.6851851851851851, 'recall': 0.6917613636363636, 'f1-score': 0.6824628156347284, 'support': 54.0}, 'weighted avg': {'precision': 0.7023319615912208, 'recall': 0.6851851851851852, 'f1-score': 0.6879075547356419, 'support': 54.0}} |
| No log | 34.0 | 68 | 0.5511 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 35.0 | 70 | 0.5582 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 36.0 | 72 | 0.5456 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 37.0 | 74 | 0.5422 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 38.0 | 76 | 0.5422 | {'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 | 39.0 | 78 | 0.5409 | {'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 | 40.0 | 80 | 0.5442 | {'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 | 41.0 | 82 | 0.5519 | {'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 | 42.0 | 84 | 0.5634 | {'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 | 43.0 | 86 | 0.5594 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 44.0 | 88 | 0.5539 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 45.0 | 90 | 0.5495 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 46.0 | 92 | 0.5479 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 47.0 | 94 | 0.5505 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 48.0 | 96 | 0.5609 | {'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 | 49.0 | 98 | 0.5618 | {'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 | 50.0 | 100 | 0.5642 | {'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 | 51.0 | 102 | 0.5520 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 52.0 | 104 | 0.5554 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 53.0 | 106 | 0.5512 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 54.0 | 108 | 0.5583 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 55.0 | 110 | 0.5543 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 56.0 | 112 | 0.5532 | {'0': {'precision': 0.6206896551724138, 'recall': 0.8181818181818182, 'f1-score': 0.7058823529411765, 'support': 22.0}, '1': {'precision': 0.84, 'recall': 0.65625, 'f1-score': 0.7368421052631579, 'support': 32.0}, 'accuracy': 0.7222222222222222, 'macro avg': {'precision': 0.7303448275862069, 'recall': 0.7372159090909092, 'f1-score': 0.7213622291021672, 'support': 54.0}, 'weighted avg': {'precision': 0.7506513409961686, 'recall': 0.7222222222222222, 'f1-score': 0.724228872835684, 'support': 54.0}} |
| No log | 57.0 | 114 | 0.5456 | {'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 | 58.0 | 116 | 0.5491 | {'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 | 59.0 | 118 | 0.5537 | {'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 | 60.0 | 120 | 0.5527 | {'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}} |
### Framework versions
- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
|