---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
model-index:
- name: bertweet-base
  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

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: 0.4738
- F1 Macro: 0.7848
- F1: 0.8370
- F1 Neg: 0.7327
- Acc: 0.7975
- Prec: 0.8631
- Recall: 0.8125
- Mcc: 0.5722

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1     | F1 Neg | Acc    | Prec   | Recall | Mcc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
| 0.6845        | 1.0   | 1161 | 0.6190          | 0.6706   | 0.7085 | 0.6328 | 0.675  | 0.8316 | 0.6172 | 0.3796 |
| 0.5137        | 2.0   | 2322 | 0.5512          | 0.7170   | 0.8366 | 0.5974 | 0.7675 | 0.7604 | 0.9297 | 0.4757 |
| 0.3724        | 3.0   | 3483 | 0.4738          | 0.7848   | 0.8370 | 0.7327 | 0.7975 | 0.8631 | 0.8125 | 0.5722 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2