Species_Identification_mBERT_fine_tuned_Train_Test
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-biomedical-clinical-es on the [LivingNER dataset] (https://temu.bsc.es/livingner/). This is a result of the PhD dissertation of Antonio Tamayo. It achieves the following results on the evaluation set:
- Loss: 0.0364
- Precision: 0.9493
- Recall: 0.9484
- F1: 0.9489
- Accuracy: 0.9957
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0038 | 1.0 | 3477 | 0.0280 | 0.9531 | 0.9279 | 0.9403 | 0.9950 |
| 0.0035 | 2.0 | 6954 | 0.0314 | 0.9415 | 0.9405 | 0.9410 | 0.9951 |
| 0.0018 | 3.0 | 10431 | 0.0346 | 0.9542 | 0.9264 | 0.9401 | 0.9951 |
| 0.0017 | 4.0 | 13908 | 0.0306 | 0.9451 | 0.9378 | 0.9414 | 0.9951 |
| 0.0004 | 5.0 | 17385 | 0.0346 | 0.9413 | 0.9509 | 0.9461 | 0.9955 |
| 0.0002 | 6.0 | 20862 | 0.0368 | 0.9507 | 0.9426 | 0.9466 | 0.9955 |
| 0.0006 | 7.0 | 24339 | 0.0364 | 0.9493 | 0.9484 | 0.9489 | 0.9957 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3