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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_3epoch10.64
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
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