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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_3epoch10.32
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_3epoch10.32
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: 2.2125
- Accuracy: 0.7450
- F1: 0.4
- Precision: 0.6146
- Recall: 0.2965
- Precision Sarcastic: 0.6146
- Recall Sarcastic: 0.2965
- F1 Sarcastic: 0.4
## 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: 32
- eval_batch_size: 32
- 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 | 87 | 1.9011 | 0.7464 | 0.5138 | 0.5706 | 0.4673 | 0.5706 | 0.4673 | 0.5138 |
| No log | 2.0 | 174 | 2.0529 | 0.7579 | 0.4510 | 0.6449 | 0.3467 | 0.6449 | 0.3467 | 0.4510 |
| No log | 3.0 | 261 | 1.6275 | 0.7594 | 0.4862 | 0.6270 | 0.3970 | 0.6270 | 0.3970 | 0.4862 |
| No log | 4.0 | 348 | 2.1947 | 0.7550 | 0.3796 | 0.6933 | 0.2613 | 0.6933 | 0.2613 | 0.3796 |
| No log | 5.0 | 435 | 1.9559 | 0.7522 | 0.4971 | 0.5944 | 0.4271 | 0.5944 | 0.4271 | 0.4971 |
| 0.0241 | 6.0 | 522 | 2.1438 | 0.7478 | 0.3902 | 0.6364 | 0.2814 | 0.6364 | 0.2814 | 0.3902 |
| 0.0241 | 7.0 | 609 | 2.0612 | 0.7550 | 0.4817 | 0.6124 | 0.3970 | 0.6124 | 0.3970 | 0.4817 |
| 0.0241 | 8.0 | 696 | 2.1265 | 0.7565 | 0.4601 | 0.6316 | 0.3618 | 0.6316 | 0.3618 | 0.4601 |
| 0.0241 | 9.0 | 783 | 2.2016 | 0.7464 | 0.4054 | 0.6186 | 0.3015 | 0.6186 | 0.3015 | 0.4054 |
| 0.0241 | 10.0 | 870 | 2.2125 | 0.7450 | 0.4 | 0.6146 | 0.2965 | 0.6146 | 0.2965 | 0.4 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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