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bert-base-spanish-wwm-cased-finetuned-ner

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bert-base-spanish-wwm-cased-finetuned-ner
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---
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-cased-finetuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: biobert_json
      type: biobert_json
      config: Biobert_json
      split: validation
      args: Biobert_json
    metrics:
    - name: Precision
      type: precision
      value: 0.9477110233699712
    - name: Recall
      type: recall
      value: 0.9651162790697675
    - name: F1
      type: f1
      value: 0.9563344640068918
    - name: Accuracy
      type: accuracy
      value: 0.9767557932263815
---

<!-- 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. -->

# bert-base-spanish-wwm-cased-finetuned-ner

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the biobert_json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1126
- Precision: 0.9477
- Recall: 0.9651
- F1: 0.9563
- Accuracy: 0.9768

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1463        | 1.0   | 1224 | 0.1119          | 0.9393    | 0.9569 | 0.9480 | 0.9726   |
| 0.0951        | 2.0   | 2448 | 0.1077          | 0.9331    | 0.9692 | 0.9508 | 0.9748   |
| 0.0635        | 3.0   | 3672 | 0.1061          | 0.9445    | 0.9696 | 0.9569 | 0.9770   |
| 0.043         | 4.0   | 4896 | 0.1072          | 0.9485    | 0.9676 | 0.9579 | 0.9772   |
| 0.0324        | 5.0   | 6120 | 0.1126          | 0.9477    | 0.9651 | 0.9563 | 0.9768   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3