---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch5
  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_3epoch5

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: 1.7195
- Accuracy: 0.7738
- F1: 0.5341
- Precision: 0.6522
- Recall: 0.4523
- Precision Sarcastic: 0.6522
- Recall Sarcastic: 0.4523
- F1 Sarcastic: 0.5341

## 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-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 1.9750          | 0.7695   | 0.4702 | 0.6893    | 0.3568 | 0.6893              | 0.3568           | 0.4702       |
| No log        | 2.0   | 348  | 1.8774          | 0.7695   | 0.5062 | 0.656     | 0.4121 | 0.656               | 0.4121           | 0.5062       |
| 0.027         | 3.0   | 522  | 2.0072          | 0.7738   | 0.5016 | 0.6810    | 0.3970 | 0.6810              | 0.3970           | 0.5016       |
| 0.027         | 4.0   | 696  | 1.6484          | 0.7622   | 0.5299 | 0.6118    | 0.4673 | 0.6118              | 0.4673           | 0.5299       |
| 0.027         | 5.0   | 870  | 1.7195          | 0.7738   | 0.5341 | 0.6522    | 0.4523 | 0.6522              | 0.4523           | 0.5341       |


### Framework versions

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