metadata
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: betoNer-biobert
results: []
betoNer-biobert
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1179
- Precision: 0.9511
- Recall: 0.9644
- F1: 0.9577
- Accuracy: 0.9773
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 306 | 0.1159 | 0.9263 | 0.9509 | 0.9384 | 0.9686 |
| 0.3168 | 2.0 | 612 | 0.1014 | 0.9358 | 0.9642 | 0.9498 | 0.9742 |
| 0.3168 | 3.0 | 918 | 0.0959 | 0.9462 | 0.9656 | 0.9558 | 0.9767 |
| 0.0777 | 4.0 | 1224 | 0.1011 | 0.9451 | 0.9661 | 0.9555 | 0.9767 |
| 0.0541 | 5.0 | 1530 | 0.1073 | 0.9512 | 0.9643 | 0.9577 | 0.9772 |
| 0.0541 | 6.0 | 1836 | 0.1083 | 0.9441 | 0.9611 | 0.9525 | 0.9751 |
| 0.0385 | 7.0 | 2142 | 0.1100 | 0.9515 | 0.9632 | 0.9573 | 0.9776 |
| 0.0385 | 8.0 | 2448 | 0.1153 | 0.9477 | 0.9658 | 0.9567 | 0.9770 |
| 0.0325 | 9.0 | 2754 | 0.1161 | 0.9495 | 0.9633 | 0.9564 | 0.9769 |
| 0.0255 | 10.0 | 3060 | 0.1179 | 0.9511 | 0.9644 | 0.9577 | 0.9773 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0