---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clasificador-twits-odio
  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. -->

# clasificador-twits-odio

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7582
- Accuracy: 0.5512

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4563        | 1.0   | 1125 | 1.3258          | 0.4973   |
| 0.318         | 2.0   | 2250 | 2.1834          | 0.4929   |
| 0.1436        | 3.0   | 3375 | 2.7582          | 0.5512   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0