---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_epoch3_batch4_lr2e-05_w0.01
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bertweet-base_epoch3_batch4_lr2e-05_w0.01

This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co./vinai/bertweet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5753
- Accuracy: 0.8687
- F1: 0.8275
- Precision: 0.8109
- Recall: 0.8448

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5235        | 1.0   | 788  | 0.4170          | 0.8643   | 0.8076 | 0.8562    | 0.7642 |
| 0.3755        | 2.0   | 1576 | 0.5068          | 0.8699   | 0.8272 | 0.8187    | 0.8358 |
| 0.2978        | 3.0   | 2364 | 0.5753          | 0.8687   | 0.8275 | 0.8109    | 0.8448 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3