---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch10.64
  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_3epoch10.64

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: 2.0926
- Accuracy: 0.7579
- F1: 0.4615
- Precision: 0.6372
- Recall: 0.3618
- Precision Sarcastic: 0.6372
- Recall Sarcastic: 0.3618
- F1 Sarcastic: 0.4615

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 44   | 2.1092          | 0.7550   | 0.4586 | 0.6261    | 0.3618 | 0.6261              | 0.3618           | 0.4586       |
| No log        | 2.0   | 88   | 1.7332          | 0.7421   | 0.4559 | 0.5769    | 0.3769 | 0.5769              | 0.3769           | 0.4559       |
| No log        | 3.0   | 132  | 1.9829          | 0.7392   | 0.4597 | 0.5662    | 0.3869 | 0.5662              | 0.3869           | 0.4597       |
| No log        | 4.0   | 176  | 1.9446          | 0.7536   | 0.3915 | 0.6707    | 0.2764 | 0.6707              | 0.2764           | 0.3915       |
| No log        | 5.0   | 220  | 1.6555          | 0.7594   | 0.4985 | 0.6194    | 0.4171 | 0.6194              | 0.4171           | 0.4985       |
| No log        | 6.0   | 264  | 1.9983          | 0.7594   | 0.4261 | 0.6739    | 0.3116 | 0.6739              | 0.3116           | 0.4261       |
| No log        | 7.0   | 308  | 1.9632          | 0.7622   | 0.4985 | 0.6308    | 0.4121 | 0.6308              | 0.4121           | 0.4985       |
| No log        | 8.0   | 352  | 2.1204          | 0.7507   | 0.4055 | 0.6413    | 0.2965 | 0.6413              | 0.2965           | 0.4055       |
| No log        | 9.0   | 396  | 2.0696          | 0.7637   | 0.4810 | 0.6496    | 0.3819 | 0.6496              | 0.3819           | 0.4810       |
| No log        | 10.0  | 440  | 2.0926          | 0.7579   | 0.4615 | 0.6372    | 0.3618 | 0.6372              | 0.3618           | 0.4615       |


### Framework versions

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