---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: irony_es_Mexico
  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. -->

# irony_es_Mexico

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0036
- Accuracy: 0.6531
- Precision: 0.5292
- Recall: 0.5686
- F1: 0.5482

## 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-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0044        | 1.0   | 129  | 0.0042          | 0.5922   | 0.448     | 0.4392 | 0.4436 |
| 0.0041        | 2.0   | 258  | 0.0041          | 0.5239   | 0.4238    | 0.7961 | 0.5531 |
| 0.0039        | 3.0   | 387  | 0.0038          | 0.5864   | 0.4615    | 0.7059 | 0.5581 |
| 0.0034        | 4.0   | 516  | 0.0034          | 0.5399   | 0.4362    | 0.8314 | 0.5722 |
| 0.003         | 5.0   | 645  | 0.0032          | 0.6241   | 0.4944    | 0.6902 | 0.5761 |
| 0.0023        | 6.0   | 774  | 0.0036          | 0.5733   | 0.4509    | 0.7020 | 0.5491 |
| 0.0022        | 7.0   | 903  | 0.0036          | 0.6531   | 0.5292    | 0.5686 | 0.5482 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1