transformers pytorch roberta text-classification generated_from_trainer base_model:vinai/phobert-base-v2 base_model:finetune:vinai/phobert-base-v2 autotrain_compatible endpoints_compatible region:us
---
base_model: vinai/phobert-base-v2
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: PhoBERT-Final_Mixed-aug_backtranslation-1
  results: []
---

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# PhoBERT-Final_Mixed-aug_backtranslation-1

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1341
- Accuracy: 0.74
- F1: 0.7394

## 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: 16
- eval_batch_size: 16
- seed: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9141        | 1.0   | 87   | 0.7614          | 0.66     | 0.6406 |
| 0.6131        | 2.0   | 174  | 0.6805          | 0.74     | 0.74   |
| 0.4267        | 3.0   | 261  | 0.7192          | 0.74     | 0.7385 |
| 0.2938        | 4.0   | 348  | 0.8398          | 0.7      | 0.6989 |
| 0.1957        | 5.0   | 435  | 0.9773          | 0.74     | 0.7385 |
| 0.158         | 6.0   | 522  | 1.0364          | 0.73     | 0.7271 |
| 0.1052        | 7.0   | 609  | 1.1180          | 0.73     | 0.73   |
| 0.0954        | 8.0   | 696  | 1.1341          | 0.74     | 0.7394 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
