---
license: mit
base_model: DeepESP/gpt2-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: SciGPT2-ft-TweetAreas-ES
  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. -->

# SciGPT2-ft-TweetAreas-ES

This model is a fine-tuned version of [DeepESP/gpt2-spanish](https://huggingface.co/DeepESP/gpt2-spanish) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2090
- Roc Auc: 0.7863
- Hamming Loss: 0.0548
- F1 Score: 0.6523
- Accuracy: 0.4083
- Precision: 0.8301
- Recall: 0.6023

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| 0.1499        | 1.0   | 747  | 0.1910          | 0.7062  | 0.0689       | 0.4861   | 0.3320   | 0.8506    | 0.4443 |
| 0.1593        | 2.0   | 1494 | 0.1707          | 0.7546  | 0.0636       | 0.5862   | 0.3494   | 0.7958    | 0.5444 |
| 0.1042        | 3.0   | 2241 | 0.1700          | 0.7718  | 0.0617       | 0.6133   | 0.3748   | 0.7891    | 0.5812 |
| 0.0455        | 4.0   | 2988 | 0.1786          | 0.7934  | 0.0585       | 0.6533   | 0.3855   | 0.7900    | 0.6232 |
| 0.0378        | 5.0   | 3735 | 0.1896          | 0.7903  | 0.0571       | 0.6564   | 0.3882   | 0.8020    | 0.6093 |
| 0.0199        | 6.0   | 4482 | 0.1948          | 0.7983  | 0.0566       | 0.6627   | 0.3949   | 0.7763    | 0.6304 |
| 0.0101        | 7.0   | 5229 | 0.2014          | 0.7888  | 0.0553       | 0.6625   | 0.3963   | 0.8127    | 0.6069 |
| 0.0087        | 8.0   | 5976 | 0.2059          | 0.7830  | 0.0563       | 0.6507   | 0.3922   | 0.8271    | 0.5969 |
| 0.0071        | 9.0   | 6723 | 0.2074          | 0.7888  | 0.0550       | 0.6587   | 0.4070   | 0.8304    | 0.6080 |
| 0.0047        | 10.0  | 7470 | 0.2090          | 0.7863  | 0.0548       | 0.6523   | 0.4083   | 0.8301    | 0.6023 |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1