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

# Twroberta-baseB_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: 0.1287
- Accuracy: 0.7957
- Precision: 0.2382
- Recall: 0.3026
- F1: 0.2661

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 217  | 0.1258          | 0.8571   | 0.0       | 0.0    | 0.0    |
| No log        | 2.0   | 434  | 0.1229          | 0.8614   | 0.3564    | 0.1624 | 0.2231 |
| 0.1621        | 3.0   | 651  | 0.1287          | 0.7957   | 0.2382    | 0.3026 | 0.2661 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1