|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# betoNer-biobert |
|
|
|
This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/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 |
|
|
