---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
model-index:
- name: bert_adaptation_resenas_de_vinos_2023_11_25_15_31
  results: []
---

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# bert_adaptation_resenas_de_vinos_2023_11_25_15_31

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: 2.6461

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9807        | 1.0   | 250  | 3.0434          |
| 3.0811        | 2.0   | 500  | 3.1461          |
| 2.7704        | 3.0   | 750  | 2.9649          |
| 2.6821        | 4.0   | 1000 | 2.8179          |
| 2.556         | 5.0   | 1250 | 2.6522          |
| 2.3324        | 6.0   | 1500 | 2.7123          |
| 2.3137        | 7.0   | 1750 | 2.5994          |
| 2.2926        | 8.0   | 2000 | 2.6741          |
| 2.1216        | 9.0   | 2250 | 2.6469          |
| 2.0317        | 10.0  | 2500 | 2.6205          |
| 2.0053        | 11.0  | 2750 | 2.4237          |
| 2.0453        | 12.0  | 3000 | 2.5970          |
| 1.9702        | 13.0  | 3250 | 2.4548          |
| 1.9147        | 14.0  | 3500 | 2.4731          |
| 1.9143        | 15.0  | 3750 | 2.4431          |
| 1.7803        | 16.0  | 4000 | 2.4247          |
| 1.7726        | 17.0  | 4250 | 2.5558          |
| 1.7448        | 18.0  | 4500 | 2.5092          |
| 1.7008        | 19.0  | 4750 | 2.4883          |
| 1.769         | 20.0  | 5000 | 2.4471          |


### Framework versions

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