---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: irony_es_United_States
  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_United_States

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: 0.0041
- Accuracy: 0.6530
- Precision: 0.4709
- Recall: 0.3716
- F1: 0.4154

## 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   | 124  | 0.0043          | 0.5266   | 0.3652    | 0.5780 | 0.4476 |
| 0.0043        | 2.0   | 248  | 0.0043          | 0.4414   | 0.3553    | 0.8394 | 0.4993 |
| 0.0043        | 3.0   | 372  | 0.0042          | 0.6377   | 0.4398    | 0.3349 | 0.3802 |
| 0.0042        | 4.0   | 496  | 0.0041          | 0.4414   | 0.3513    | 0.8073 | 0.4896 |
| 0.004         | 5.0   | 620  | 0.0040          | 0.4840   | 0.3676    | 0.7706 | 0.4978 |
| 0.0036        | 6.0   | 744  | 0.0036          | 0.6499   | 0.4764    | 0.5550 | 0.5127 |
| 0.0031        | 7.0   | 868  | 0.0040          | 0.5297   | 0.3959    | 0.7936 | 0.5282 |
| 0.0024        | 8.0   | 992  | 0.0041          | 0.6530   | 0.4709    | 0.3716 | 0.4154 |


### Framework versions

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