---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Twroberta-baseB_5epoch
  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_5epoch

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: 0.1414
- Accuracy: 0.7971
- Precision: 0.2686
- Recall: 0.3395
- F1: 0.2984

## 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 217  | 0.1259          | 0.8571   | 0.0       | 0.0    | 0.0    |
| No log        | 2.0   | 434  | 0.1252          | 0.8579   | 0.3690    | 0.0185 | 0.0351 |
| 0.1645        | 3.0   | 651  | 0.1203          | 0.8414   | 0.2958    | 0.2066 | 0.2431 |
| 0.1645        | 4.0   | 868  | 0.1383          | 0.7686   | 0.2221    | 0.3616 | 0.2751 |
| 0.0952        | 5.0   | 1085 | 0.1414          | 0.7971   | 0.2686    | 0.3395 | 0.2984 |


### Framework versions

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