---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-uncased-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-spanish-wwm-uncased-ner

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3905
- Precision: 0.8768
- Recall: 0.9067
- F1: 0.8915
- Accuracy: 0.9376

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 280  | 0.2690          | 0.8236    | 0.8578 | 0.8403 | 0.9268   |
| 0.3996        | 2.0   | 560  | 0.2917          | 0.8116    | 0.8681 | 0.8389 | 0.9180   |
| 0.3996        | 3.0   | 840  | 0.2715          | 0.8495    | 0.8696 | 0.8594 | 0.9319   |
| 0.118         | 4.0   | 1120 | 0.2914          | 0.8567    | 0.9037 | 0.8796 | 0.9370   |
| 0.118         | 5.0   | 1400 | 0.3040          | 0.8454    | 0.8993 | 0.8715 | 0.9330   |
| 0.0608        | 6.0   | 1680 | 0.2979          | 0.8631    | 0.8963 | 0.8794 | 0.9359   |
| 0.0608        | 7.0   | 1960 | 0.3376          | 0.8653    | 0.8948 | 0.8798 | 0.9322   |
| 0.0353        | 8.0   | 2240 | 0.3283          | 0.8622    | 0.9081 | 0.8846 | 0.9370   |
| 0.0236        | 9.0   | 2520 | 0.3584          | 0.8575    | 0.9007 | 0.8786 | 0.9351   |
| 0.0236        | 10.0  | 2800 | 0.3891          | 0.8813    | 0.9022 | 0.8917 | 0.9346   |
| 0.0155        | 11.0  | 3080 | 0.3678          | 0.8764    | 0.9037 | 0.8899 | 0.9381   |
| 0.0155        | 12.0  | 3360 | 0.3736          | 0.8759    | 0.9096 | 0.8924 | 0.9386   |
| 0.0123        | 13.0  | 3640 | 0.4030          | 0.8721    | 0.8993 | 0.8855 | 0.9349   |
| 0.0123        | 14.0  | 3920 | 0.3890          | 0.8768    | 0.9067 | 0.8915 | 0.9373   |
| 0.0123        | 15.0  | 4200 | 0.3905          | 0.8768    | 0.9067 | 0.8915 | 0.9376   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1