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---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: twitter-roberta-base_3epoch10.8
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_3epoch10.8
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: 2.3313
- Accuracy: 0.7579
- F1: 0.4324
- Precision: 0.6598
- Recall: 0.3216
- Precision Sarcastic: 0.6598
- Recall Sarcastic: 0.3216
- F1 Sarcastic: 0.4324
## 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: 8
- eval_batch_size: 8
- 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 | 347 | 2.2730 | 0.7464 | 0.4568 | 0.592 | 0.3719 | 0.592 | 0.3719 | 0.4568 |
| 0.0571 | 2.0 | 694 | 1.9955 | 0.7594 | 0.3971 | 0.7051 | 0.2764 | 0.7051 | 0.2764 | 0.3971 |
| 0.0756 | 3.0 | 1041 | 1.9672 | 0.7421 | 0.4526 | 0.5781 | 0.3719 | 0.5781 | 0.3719 | 0.4526 |
| 0.0756 | 4.0 | 1388 | 2.0562 | 0.7493 | 0.4695 | 0.5969 | 0.3869 | 0.5969 | 0.3869 | 0.4695 |
| 0.0421 | 5.0 | 1735 | 2.2045 | 0.7522 | 0.4416 | 0.6239 | 0.3417 | 0.6239 | 0.3417 | 0.4416 |
| 0.0268 | 6.0 | 2082 | 2.2693 | 0.7594 | 0.4099 | 0.6905 | 0.2915 | 0.6905 | 0.2915 | 0.4099 |
| 0.0268 | 7.0 | 2429 | 2.1746 | 0.7536 | 0.4466 | 0.6273 | 0.3467 | 0.6273 | 0.3467 | 0.4466 |
| 0.0145 | 8.0 | 2776 | 2.3412 | 0.7550 | 0.4178 | 0.6559 | 0.3065 | 0.6559 | 0.3065 | 0.4178 |
| 0.0051 | 9.0 | 3123 | 2.3512 | 0.7565 | 0.4232 | 0.6596 | 0.3116 | 0.6596 | 0.3116 | 0.4232 |
| 0.0051 | 10.0 | 3470 | 2.3313 | 0.7579 | 0.4324 | 0.6598 | 0.3216 | 0.6598 | 0.3216 | 0.4324 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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