---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch10
  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. -->

# bertweet-base_3epoch10

This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7005
- Accuracy: 0.7392
- F1: 0.4217
- Precision: 0.5789
- Recall: 0.3317
- Precision Sarcastic: 0.5789
- Recall Sarcastic: 0.3317
- F1 Sarcastic: 0.4217

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 1.3971          | 0.7493   | 0.4    | 0.6374    | 0.2915 | 0.6374              | 0.2915           | 0.4          |
| No log        | 2.0   | 348  | 1.0371          | 0.7334   | 0.3854 | 0.5686    | 0.2915 | 0.5686              | 0.2915           | 0.3854       |
| 0.0617        | 3.0   | 522  | 1.6060          | 0.7147   | 0.4277 | 0.5034    | 0.3719 | 0.5034              | 0.3719           | 0.4277       |
| 0.0617        | 4.0   | 696  | 1.3603          | 0.7464   | 0.4172 | 0.6117    | 0.3166 | 0.6117              | 0.3166           | 0.4172       |
| 0.0617        | 5.0   | 870  | 1.5872          | 0.7478   | 0.4373 | 0.6071    | 0.3417 | 0.6071              | 0.3417           | 0.4373       |
| 0.032         | 6.0   | 1044 | 1.4206          | 0.7493   | 0.3916 | 0.6437    | 0.2814 | 0.6437              | 0.2814           | 0.3916       |
| 0.032         | 7.0   | 1218 | 1.4775          | 0.7507   | 0.4055 | 0.6413    | 0.2965 | 0.6413              | 0.2965           | 0.4055       |
| 0.032         | 8.0   | 1392 | 1.5835          | 0.7421   | 0.4389 | 0.5833    | 0.3518 | 0.5833              | 0.3518           | 0.4389       |
| 0.0125        | 9.0   | 1566 | 1.7009          | 0.7464   | 0.3846 | 0.6322    | 0.2764 | 0.6322              | 0.2764           | 0.3846       |
| 0.0125        | 10.0  | 1740 | 1.7005          | 0.7392   | 0.4217 | 0.5789    | 0.3317 | 0.5789              | 0.3317           | 0.4217       |


### Framework versions

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