README.md

---
base_model: vinai/bertweet-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-large_epoch6_batch4_lr2e-05_w0.005
  results: []
---

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# bertweet-large_epoch6_batch4_lr2e-05_w0.005

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: 0.5716
- Accuracy: 0.6274
- F1: 0.0
- Precision: 0.0
- Recall: 0.0

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
| 0.7185        | 1.0   | 788  | 0.6708          | 0.6274   | 0.0 | 0.0       | 0.0    |
| 0.6791        | 2.0   | 1576 | 0.6699          | 0.6274   | 0.0 | 0.0       | 0.0    |
| 0.6781        | 3.0   | 2364 | 0.8322          | 0.6274   | 0.0 | 0.0       | 0.0    |
| 0.6609        | 4.0   | 3152 | 0.7472          | 0.6274   | 0.0 | 0.0       | 0.0    |
| 0.6673        | 5.0   | 3940 | 0.6602          | 0.6274   | 0.0 | 0.0       | 0.0    |
| 0.6166        | 6.0   | 4728 | 0.5716          | 0.6274   | 0.0 | 0.0       | 0.0    |


### Framework versions

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