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---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Twroberta-baseB_5epoch
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. -->
# Twroberta-baseB_5epoch
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: 0.1520
- Accuracy: 0.7793
- F1: 0.2545
- Precision: 0.2289
- Recall: 0.2878
- Precision Sarcastic: 0.3258
- Recall Sarcastic: 0.4
- F1 Sarcastic: 0.3591
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log | 1.0 | 217 | 0.1224 | 0.8571 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 434 | 0.1224 | 0.8686 | 0.2294 | 0.4139 | 0.1587 | 0.6232 | 0.2389 | 0.3454 |
| 0.1581 | 3.0 | 651 | 0.1277 | 0.7979 | 0.2474 | 0.2290 | 0.2694 | 0.3380 | 0.4 | 0.3664 |
| 0.1581 | 4.0 | 868 | 0.1438 | 0.7914 | 0.2503 | 0.2424 | 0.2620 | 0.3137 | 0.3556 | 0.3333 |
| 0.0781 | 5.0 | 1085 | 0.1520 | 0.7793 | 0.2545 | 0.2289 | 0.2878 | 0.3258 | 0.4 | 0.3591 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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