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---
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-cased-ner
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. -->
# bert-base-spanish-wwm-cased-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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3695
- Precision: 0.8640
- Recall: 0.9126
- F1: 0.8876
- Accuracy: 0.9378
## 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 | 0.3016 | 0.7779 | 0.8252 | 0.8009 | 0.9052 |
| 0.4113 | 2.0 | 560 | 0.2671 | 0.8150 | 0.8681 | 0.8407 | 0.9248 |
| 0.4113 | 3.0 | 840 | 0.2747 | 0.8181 | 0.8593 | 0.8382 | 0.9268 |
| 0.1179 | 4.0 | 1120 | 0.2875 | 0.8336 | 0.8978 | 0.8645 | 0.9312 |
| 0.1179 | 5.0 | 1400 | 0.3087 | 0.8529 | 0.9022 | 0.8769 | 0.9361 |
| 0.0608 | 6.0 | 1680 | 0.3449 | 0.8645 | 0.8978 | 0.8808 | 0.9351 |
| 0.0608 | 7.0 | 1960 | 0.3478 | 0.8539 | 0.8919 | 0.8725 | 0.9337 |
| 0.0306 | 8.0 | 2240 | 0.3495 | 0.8426 | 0.8963 | 0.8686 | 0.9337 |
| 0.0231 | 9.0 | 2520 | 0.3812 | 0.8660 | 0.9096 | 0.8873 | 0.9366 |
| 0.0231 | 10.0 | 2800 | 0.3346 | 0.8473 | 0.8963 | 0.8711 | 0.9386 |
| 0.0174 | 11.0 | 3080 | 0.3721 | 0.8583 | 0.9067 | 0.8818 | 0.9373 |
| 0.0174 | 12.0 | 3360 | 0.3778 | 0.8632 | 0.9067 | 0.8844 | 0.9371 |
| 0.014 | 13.0 | 3640 | 0.3733 | 0.8624 | 0.9096 | 0.8854 | 0.9366 |
| 0.014 | 14.0 | 3920 | 0.3709 | 0.8652 | 0.9126 | 0.8882 | 0.9398 |
| 0.013 | 15.0 | 4200 | 0.3695 | 0.8640 | 0.9126 | 0.8876 | 0.9378 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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