transformers safetensors electra text-classification classification generated_from_trainer es dataset:somosnlp-hackathon-2022/es_tweets_laboral base_model:mrm8488/electricidad-base-discriminator base_model:finetune:mrm8488/electricidad-base-discriminator autotrain_compatible endpoints_compatible region:us
---
base_model: mrm8488/electricidad-base-discriminator
datasets:
- somosnlp-hackathon-2022/es_tweets_laboral
language:
- es
library_name: transformers
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- classification
- generated_from_trainer
model-index:
- name: clasificador-tweets
  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-tweets

This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the somosnlp-hackathon-2022/es_tweets_laboral dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4954
- Accuracy: 0.7021

## Intended uses & limitations

This model is intended for the task Text Classification.

## Training and evaluation data

We used the somosnlp-hackathon-2022/es_tweets_laboral dataset.

## 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 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 23   | 1.2185          | 0.6383   |
| No log        | 2.0   | 46   | 1.2849          | 0.6596   |
| No log        | 3.0   | 69   | 1.4492          | 0.5957   |
| No log        | 4.0   | 92   | 1.1863          | 0.7234   |
| No log        | 5.0   | 115  | 1.5050          | 0.6383   |
| No log        | 6.0   | 138  | 1.4848          | 0.6383   |
| No log        | 7.0   | 161  | 1.5045          | 0.7021   |
| No log        | 8.0   | 184  | 1.5510          | 0.6809   |
| No log        | 9.0   | 207  | 1.4867          | 0.7021   |
| No log        | 10.0  | 230  | 1.4954          | 0.7021   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0