---
base_model: vinai/bertweet-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-large_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-large_epoch3_batch4_lr2e-05_w0.01

This model is a fine-tuned version of [vinai/bertweet-large](https://huggingface.co/vinai/bertweet-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5167
- Accuracy: 0.9066
- F1: 0.8768
- Precision: 0.8617
- Recall: 0.8925

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6423        | 1.0   | 788  | 0.4273          | 0.8966   | 0.8597 | 0.8689    | 0.8507 |
| 0.4072        | 2.0   | 1576 | 0.5435          | 0.8910   | 0.8600 | 0.8247    | 0.8985 |
| 0.2823        | 3.0   | 2364 | 0.5167          | 0.9066   | 0.8768 | 0.8617    | 0.8925 |


### Framework versions

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