---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch5.64
  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_3epoch5.64

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: 2.2330
- Accuracy: 0.7478
- F1: 0.4147
- Precision: 0.62
- Recall: 0.3116
- Precision Sarcastic: 0.62
- Recall Sarcastic: 0.3116
- F1 Sarcastic: 0.4147

## 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: 64
- eval_batch_size: 64
- 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   | 44   | 2.1672          | 0.7262   | 0.5103 | 0.5238    | 0.4975 | 0.5238              | 0.4975           | 0.5103       |
| No log        | 2.0   | 88   | 2.2472          | 0.7522   | 0.4150 | 0.6421    | 0.3065 | 0.6421              | 0.3065           | 0.4150       |
| No log        | 3.0   | 132  | 2.2529          | 0.7464   | 0.4359 | 0.6018    | 0.3417 | 0.6018              | 0.3417           | 0.4359       |
| No log        | 4.0   | 176  | 2.2045          | 0.7522   | 0.4522 | 0.6174    | 0.3568 | 0.6174              | 0.3568           | 0.4522       |
| No log        | 5.0   | 220  | 2.2330          | 0.7478   | 0.4147 | 0.62      | 0.3116 | 0.62                | 0.3116           | 0.4147       |


### Framework versions

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