---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch10.16
  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_3epoch10.16

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: 2.1539
- Accuracy: 0.7478
- F1: 0.4224
- Precision: 0.6154
- Recall: 0.3216
- Precision Sarcastic: 0.6154
- Recall Sarcastic: 0.3216
- F1 Sarcastic: 0.4224

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 2.1148          | 0.7493   | 0.2869 | 0.7778    | 0.1759 | 0.7778              | 0.1759           | 0.2869       |
| No log        | 2.0   | 348  | 1.2416          | 0.7320   | 0.3882 | 0.5619    | 0.2965 | 0.5619              | 0.2965           | 0.3882       |
| 0.0732        | 3.0   | 522  | 1.5725          | 0.7392   | 0.4873 | 0.5584    | 0.4322 | 0.5584              | 0.4322           | 0.4873       |
| 0.0732        | 4.0   | 696  | 1.7604          | 0.7450   | 0.4520 | 0.5887    | 0.3668 | 0.5887              | 0.3668           | 0.4520       |
| 0.0732        | 5.0   | 870  | 1.9529          | 0.7291   | 0.4749 | 0.5346    | 0.4271 | 0.5346              | 0.4271           | 0.4749       |
| 0.0278        | 6.0   | 1044 | 1.7258          | 0.7334   | 0.4699 | 0.5467    | 0.4121 | 0.5467              | 0.4121           | 0.4699       |
| 0.0278        | 7.0   | 1218 | 2.0437          | 0.7464   | 0.4568 | 0.592     | 0.3719 | 0.592               | 0.3719           | 0.4568       |
| 0.0278        | 8.0   | 1392 | 2.0771          | 0.7507   | 0.4508 | 0.6121    | 0.3568 | 0.6121              | 0.3568           | 0.4508       |
| 0.0081        | 9.0   | 1566 | 2.1414          | 0.7478   | 0.4186 | 0.6176    | 0.3166 | 0.6176              | 0.3166           | 0.4186       |
| 0.0081        | 10.0  | 1740 | 2.1539          | 0.7478   | 0.4224 | 0.6154    | 0.3216 | 0.6154              | 0.3216           | 0.4224       |


### Framework versions

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