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longformer-base-4096-bne-es-finetuned-v2
This model is a fine-tuned version of joheras/longformer-base-4096-bne-es-finetuned-clinais on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0205
- Precision: 0.4420
- Recall: 0.6075
- F1: 0.5117
- Accuracy: 0.8420
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 196 | 0.6855 | 0.1500 | 0.2840 | 0.1963 | 0.7991 |
| No log | 2.0 | 392 | 0.5677 | 0.2372 | 0.3962 | 0.2967 | 0.8271 |
| 0.7365 | 3.0 | 588 | 0.5457 | 0.3043 | 0.5142 | 0.3823 | 0.8412 |
| 0.7365 | 4.0 | 784 | 0.5818 | 0.3268 | 0.5208 | 0.4016 | 0.8303 |
| 0.7365 | 5.0 | 980 | 0.5958 | 0.3595 | 0.5538 | 0.4359 | 0.8385 |
| 0.3443 | 6.0 | 1176 | 0.6380 | 0.3916 | 0.5660 | 0.4630 | 0.8396 |
| 0.3443 | 7.0 | 1372 | 0.6835 | 0.3499 | 0.5594 | 0.4305 | 0.8272 |
| 0.2031 | 8.0 | 1568 | 0.6758 | 0.4088 | 0.5726 | 0.4770 | 0.8441 |
| 0.2031 | 9.0 | 1764 | 0.7236 | 0.3921 | 0.5792 | 0.4676 | 0.8397 |
| 0.2031 | 10.0 | 1960 | 0.7699 | 0.3941 | 0.5755 | 0.4678 | 0.8349 |
| 0.1283 | 11.0 | 2156 | 0.7788 | 0.4004 | 0.5745 | 0.4719 | 0.8315 |
| 0.1283 | 12.0 | 2352 | 0.7802 | 0.4164 | 0.6019 | 0.4923 | 0.8479 |
| 0.0861 | 13.0 | 2548 | 0.8092 | 0.4280 | 0.5915 | 0.4966 | 0.8394 |
| 0.0861 | 14.0 | 2744 | 0.8582 | 0.4211 | 0.5991 | 0.4945 | 0.8373 |
| 0.0861 | 15.0 | 2940 | 0.8581 | 0.3860 | 0.5925 | 0.4674 | 0.8407 |
| 0.0589 | 16.0 | 3136 | 0.9137 | 0.4213 | 0.6038 | 0.4963 | 0.8291 |
| 0.0589 | 17.0 | 3332 | 0.8669 | 0.4287 | 0.6038 | 0.5014 | 0.8448 |
| 0.0436 | 18.0 | 3528 | 0.8987 | 0.4365 | 0.6028 | 0.5063 | 0.8403 |
| 0.0436 | 19.0 | 3724 | 0.9389 | 0.4437 | 0.5991 | 0.5098 | 0.8360 |
| 0.0436 | 20.0 | 3920 | 0.9512 | 0.4479 | 0.6 | 0.5129 | 0.8348 |
| 0.0313 | 21.0 | 4116 | 0.9484 | 0.4535 | 0.6075 | 0.5194 | 0.8445 |
| 0.0313 | 22.0 | 4312 | 0.9715 | 0.4498 | 0.6123 | 0.5186 | 0.8438 |
| 0.0236 | 23.0 | 4508 | 0.9726 | 0.4542 | 0.6170 | 0.5232 | 0.8457 |
| 0.0236 | 24.0 | 4704 | 0.9586 | 0.4531 | 0.6066 | 0.5188 | 0.8427 |
| 0.0236 | 25.0 | 4900 | 0.9962 | 0.4634 | 0.6160 | 0.5290 | 0.8433 |
| 0.0206 | 26.0 | 5096 | 1.0098 | 0.4683 | 0.6198 | 0.5335 | 0.8429 |
| 0.0206 | 27.0 | 5292 | 0.9914 | 0.4527 | 0.6094 | 0.5195 | 0.8414 |
| 0.0206 | 28.0 | 5488 | 1.0146 | 0.4567 | 0.6113 | 0.5228 | 0.8436 |
| 0.0154 | 29.0 | 5684 | 1.0199 | 0.4468 | 0.6104 | 0.5159 | 0.8428 |
| 0.0154 | 30.0 | 5880 | 1.0205 | 0.4420 | 0.6075 | 0.5117 | 0.8420 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
