---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
datasets:
- muchocine
metrics:
- accuracy
model-index:
- name: bert-base-uncased-es-sentiment-analysis
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: muchocine
      type: muchocine
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.792258064516129
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-es-sentiment-analysis

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the muchocine dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9713
- Accuracy: 0.7923

## 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: 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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.541         | 1.0   | 49   | 0.4618          | 0.7781   |
| 0.3157        | 2.0   | 98   | 0.4989          | 0.7742   |
| 0.1294        | 3.0   | 147  | 0.6931          | 0.8      |
| 0.0541        | 4.0   | 196  | 0.8284          | 0.7935   |
| 0.0254        | 5.0   | 245  | 0.9713          | 0.7923   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1