---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch7
  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_3epoch7

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: 1.3665
- Accuracy: 0.7493
- F1: 0.4562
- Precision: 0.6033
- Recall: 0.3668
- Precision Sarcastic: 0.6033
- Recall Sarcastic: 0.3668
- F1 Sarcastic: 0.4562

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 0.9738          | 0.7378   | 0.2541 | 0.6889    | 0.1558 | 0.6889              | 0.1558           | 0.2541       |
| No log        | 2.0   | 348  | 1.0669          | 0.7565   | 0.4459 | 0.6415    | 0.3417 | 0.6415              | 0.3417           | 0.4459       |
| 0.1251        | 3.0   | 522  | 1.2051          | 0.7493   | 0.4082 | 0.6316    | 0.3015 | 0.6316              | 0.3015           | 0.4082       |
| 0.1251        | 4.0   | 696  | 1.2494          | 0.7507   | 0.4401 | 0.6182    | 0.3417 | 0.6182              | 0.3417           | 0.4401       |
| 0.1251        | 5.0   | 870  | 1.3273          | 0.7507   | 0.4677 | 0.6032    | 0.3819 | 0.6032              | 0.3819           | 0.4677       |
| 0.0458        | 6.0   | 1044 | 1.3478          | 0.7493   | 0.4759 | 0.5940    | 0.3970 | 0.5940              | 0.3970           | 0.4759       |
| 0.0458        | 7.0   | 1218 | 1.3665          | 0.7493   | 0.4562 | 0.6033    | 0.3668 | 0.6033              | 0.3668           | 0.4562       |


### Framework versions

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