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---
library_name: transformers
license: mit
base_model: vinai/bartpho-word
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine-tuning_BARTPho
  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. -->

# fine-tuning_BARTPho

This model is a fine-tuned version of [vinai/bartpho-word](https://huggingface.co/vinai/bartpho-word) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1876
- Accuracy: 0.014
- F1: 0.0011

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 3.7202        | 1.0   | 125  | 1.3840          | 0.016    | 0.0018 |
| 1.3287        | 2.0   | 250  | 1.2517          | 0.014    | 0.0011 |
| 1.2451        | 3.0   | 375  | 1.2197          | 0.016    | 0.0015 |
| 1.2059        | 4.0   | 500  | 1.2077          | 0.014    | 0.0011 |
| 1.105         | 5.0   | 625  | 1.2053          | 0.014    | 0.0011 |
| 1.1054        | 6.0   | 750  | 1.1893          | 0.018    | 0.0015 |
| 1.1207        | 7.0   | 875  | 1.1881          | 0.022    | 0.0045 |
| 1.1011        | 8.0   | 1000 | 1.1857          | 0.016    | 0.0025 |
| 1.0578        | 9.0   | 1125 | 1.1877          | 0.016    | 0.0031 |
| 1.0836        | 10.0  | 1250 | 1.1876          | 0.014    | 0.0011 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3