---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
model-index:
- name: bert_adaptation_martin_fierro
  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_adaptation_martin_fierro

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6952

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.3685        | 1.0   | 58   | 4.8544          |
| 4.3651        | 2.0   | 116  | 4.4985          |
| 3.8868        | 3.0   | 174  | 3.7412          |
| 3.7072        | 4.0   | 232  | 3.7141          |
| 3.7598        | 5.0   | 290  | 3.8915          |
| 3.5408        | 6.0   | 348  | 3.9818          |
| 3.3939        | 7.0   | 406  | 4.0336          |
| 3.4642        | 8.0   | 464  | 3.8640          |
| 3.2745        | 9.0   | 522  | 3.9118          |
| 3.177         | 10.0  | 580  | 3.8540          |
| 3.2224        | 11.0  | 638  | 3.8703          |
| 3.1109        | 12.0  | 696  | 3.7848          |
| 2.9985        | 13.0  | 754  | 3.5726          |
| 3.0286        | 14.0  | 812  | 3.8872          |
| 3.0456        | 15.0  | 870  | 3.8465          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0