---
base_model: vinai/bertweet-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-large_2_4_2e-05_0.01
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bertweet-large_2_4_2e-05_0.01

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: 0.4839
- Accuracy: 0.9021
- F1: 0.8675
- Precision: 0.8754
- Recall: 0.8597

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4682        | 1.0   | 2317 | 0.4096          | 0.8943   | 0.8554 | 0.8727    | 0.8388 |
| 0.1787        | 2.0   | 4634 | 0.4839          | 0.9021   | 0.8675 | 0.8754    | 0.8597 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3