---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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: 0.1520
- Accuracy: 0.7793
- F1: 0.2545
- Precision: 0.2289
- Recall: 0.2878
- Precision Sarcastic: 0.3258
- Recall Sarcastic: 0.4
- F1 Sarcastic: 0.3591

## 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   | 217  | 0.1224          | 0.8571   | 0.0    | 0.0       | 0.0    | 0.0                 | 0.0              | 0.0          |
| No log        | 2.0   | 434  | 0.1224          | 0.8686   | 0.2294 | 0.4139    | 0.1587 | 0.6232              | 0.2389           | 0.3454       |
| 0.1581        | 3.0   | 651  | 0.1277          | 0.7979   | 0.2474 | 0.2290    | 0.2694 | 0.3380              | 0.4              | 0.3664       |
| 0.1581        | 4.0   | 868  | 0.1438          | 0.7914   | 0.2503 | 0.2424    | 0.2620 | 0.3137              | 0.3556           | 0.3333       |
| 0.0781        | 5.0   | 1085 | 0.1520          | 0.7793   | 0.2545 | 0.2289    | 0.2878 | 0.3258              | 0.4              | 0.3591       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1