estudiante_MC318_VIOPERU
This model is a fine-tuned version of on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5975
- Accuracy: 0.75
- F1: 0.7499
- Precision: 0.7503
- Recall: 0.75
- Roc Auc: 0.8064
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-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 21
- training_steps: 210
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
Precision |
Recall |
Roc Auc |
| 0.6651 |
1.0095 |
10 |
0.7186 |
0.3214 |
0.2432 |
0.1957 |
0.3214 |
0.3023 |
| 0.6966 |
2.0190 |
20 |
0.7151 |
0.375 |
0.3267 |
0.3247 |
0.375 |
0.3724 |
| 0.6205 |
3.0286 |
30 |
0.7197 |
0.4643 |
0.4385 |
0.4562 |
0.4643 |
0.4554 |
| 0.6278 |
4.0381 |
40 |
0.7118 |
0.4821 |
0.4614 |
0.4789 |
0.4821 |
0.4994 |
| 0.5792 |
6.0095 |
50 |
0.6974 |
0.5536 |
0.5465 |
0.5571 |
0.5536 |
0.5357 |
| 0.5719 |
7.0190 |
60 |
0.6983 |
0.5893 |
0.5860 |
0.5922 |
0.5893 |
0.5638 |
| 0.5582 |
8.0286 |
70 |
0.6902 |
0.6071 |
0.6026 |
0.6123 |
0.6071 |
0.5912 |
| 0.5299 |
9.0381 |
80 |
0.6977 |
0.5893 |
0.5828 |
0.5952 |
0.5893 |
0.6059 |
| 0.5262 |
11.0095 |
90 |
0.6972 |
0.6429 |
0.6424 |
0.6436 |
0.6429 |
0.6224 |
| 0.4854 |
12.0190 |
100 |
0.6974 |
0.625 |
0.6239 |
0.6265 |
0.625 |
0.6416 |
| 0.463 |
13.0286 |
110 |
0.6561 |
0.5893 |
0.5892 |
0.5894 |
0.5893 |
0.6556 |
| 0.4543 |
14.0381 |
120 |
0.6376 |
0.625 |
0.6239 |
0.6265 |
0.625 |
0.6696 |
| 0.4127 |
16.0095 |
130 |
0.6716 |
0.6964 |
0.6916 |
0.7095 |
0.6964 |
0.6849 |
| 0.4125 |
17.0190 |
140 |
0.6945 |
0.6429 |
0.6424 |
0.6436 |
0.6429 |
0.6926 |
| 0.3985 |
18.0286 |
150 |
0.6841 |
0.6786 |
0.6769 |
0.6823 |
0.6786 |
0.7092 |
| 0.3954 |
19.0381 |
160 |
0.6239 |
0.6786 |
0.6786 |
0.6786 |
0.6786 |
0.7105 |
| 0.3474 |
21.0095 |
170 |
0.6424 |
0.7143 |
0.7139 |
0.7154 |
0.7143 |
0.7092 |
| 0.3339 |
22.0190 |
180 |
0.6594 |
0.7143 |
0.7139 |
0.7154 |
0.7143 |
0.7117 |
| 0.3295 |
23.0286 |
190 |
0.7352 |
0.6429 |
0.6424 |
0.6436 |
0.6429 |
0.7079 |
| 0.3323 |
24.0381 |
200 |
0.6903 |
0.6607 |
0.6606 |
0.6609 |
0.6607 |
0.7117 |
| 0.2761 |
26.0095 |
210 |
0.6788 |
0.6607 |
0.6606 |
0.6609 |
0.6607 |
0.7181 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.2
