---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: bert-salvadoran-news
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# bert-salvadoran-news

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.4210
- Validation Loss: 1.5456
- Epoch: 19

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.1106     | 1.9331          | 0     |
| 1.9666     | 1.7924          | 1     |
| 1.8643     | 1.7777          | 2     |
| 1.8090     | 1.7018          | 3     |
| 1.7668     | 1.7372          | 4     |
| 1.7337     | 1.6726          | 5     |
| 1.6948     | 1.6624          | 6     |
| 1.6584     | 1.6863          | 7     |
| 1.6232     | 1.6174          | 8     |
| 1.5996     | 1.6399          | 9     |
| 1.5805     | 1.5340          | 10    |
| 1.5622     | 1.6202          | 11    |
| 1.5124     | 1.6176          | 12    |
| 1.5150     | 1.5644          | 13    |
| 1.5151     | 1.6002          | 14    |
| 1.4730     | 1.5746          | 15    |
| 1.4538     | 1.5536          | 16    |
| 1.4507     | 1.5537          | 17    |
| 1.4476     | 1.5450          | 18    |
| 1.4210     | 1.5456          | 19    |


### Framework versions

- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2