---
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: beto_prostata_bs32
  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. -->

# beto_prostata_bs32

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: 0.0316
- Precision: 0.9555
- Recall: 0.9604
- F1: 0.9579
- Accuracy: 0.9930

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 98   | 0.1336          | 0.7865    | 0.8320 | 0.8086 | 0.9672   |
| No log        | 2.0   | 196  | 0.0542          | 0.9314    | 0.9277 | 0.9295 | 0.9885   |
| No log        | 3.0   | 294  | 0.0318          | 0.9551    | 0.9551 | 0.9551 | 0.9928   |
| No log        | 4.0   | 392  | 0.0311          | 0.9455    | 0.9609 | 0.9532 | 0.9924   |
| No log        | 5.0   | 490  | 0.0292          | 0.9696    | 0.9759 | 0.9727 | 0.9946   |
| 0.1972        | 6.0   | 588  | 0.0267          | 0.9772    | 0.9753 | 0.9762 | 0.9953   |
| 0.1972        | 7.0   | 686  | 0.0257          | 0.9753    | 0.9753 | 0.9753 | 0.9952   |
| 0.1972        | 8.0   | 784  | 0.0259          | 0.9810    | 0.9766 | 0.9788 | 0.9956   |


### Framework versions

- Transformers 5.10.2
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2