pytorch tensorboard bert text-classification transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-spanish-wwm-cased-finetuned-NLP-IE-4
  results: []
---

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# bert-base-spanish-wwm-cased-finetuned-NLP-IE-4

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7825
- Accuracy: 0.4931

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7005        | 1.0   | 9    | 0.6977          | 0.5069   |
| 0.65          | 2.0   | 18   | 0.7035          | 0.4861   |
| 0.6144        | 3.0   | 27   | 0.7189          | 0.4722   |
| 0.5898        | 4.0   | 36   | 0.7859          | 0.4861   |
| 0.561         | 5.0   | 45   | 0.7825          | 0.4931   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
