---
base_model: MMG/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es-finetuned-sqac
tags:
- generated_from_trainer
model-index:
- name: uda_rules_qa
  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. -->

# uda_rules_qa

This model is a fine-tuned version of [MMG/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es-finetuned-sqac](https://huggingface.co/MMG/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es-finetuned-sqac) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5263

## 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: 5e-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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2609        | 1.0   | 22   | 1.0845          |
| 0.5942        | 2.0   | 44   | 0.8048          |
| 0.2471        | 3.0   | 66   | 0.5481          |
| 0.108         | 4.0   | 88   | 0.5052          |
| 0.0665        | 5.0   | 110  | 0.5149          |
| 0.0612        | 6.0   | 132  | 0.6101          |
| 0.0265        | 7.0   | 154  | 0.7251          |
| 0.0457        | 8.0   | 176  | 0.5007          |
| 0.0108        | 9.0   | 198  | 0.4987          |
| 0.0037        | 10.0  | 220  | 0.5012          |
| 0.0013        | 11.0  | 242  | 0.5184          |
| 0.0053        | 12.0  | 264  | 0.5087          |
| 0.0002        | 13.0  | 286  | 0.5167          |
| 0.0003        | 14.0  | 308  | 0.5225          |
| 0.0004        | 15.0  | 330  | 0.5263          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0