---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch
  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. -->

# twitter-roberta-base_3epoch

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9201
- Accuracy: 0.7723
- F1: 0.5183
- Precision: 0.6589
- Recall: 0.4271
- Precision Sarcastic: 0.6589
- Recall Sarcastic: 0.4271
- F1 Sarcastic: 0.5183

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 0.6210          | 0.7248   | 0.1116 | 0.75      | 0.0603 | 0.75                | 0.0603           | 0.1116       |
| No log        | 2.0   | 348  | 0.5732          | 0.7767   | 0.5016 | 0.6964    | 0.3920 | 0.6964              | 0.3920           | 0.5016       |
| 0.3415        | 3.0   | 522  | 0.9201          | 0.7723   | 0.5183 | 0.6589    | 0.4271 | 0.6589              | 0.4271           | 0.5183       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1