---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-train-aug_insert_w2v
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# PhoBERT-train-aug_insert_w2v

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: 1.2218
- Accuracy: 0.71
- F1: 0.7185

## 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: 42
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.861         | 1.0   | 85   | 0.7003          | 0.71     | 0.6826 |
| 0.532         | 2.0   | 170  | 0.6556          | 0.73     | 0.7305 |
| 0.361         | 3.0   | 255  | 0.7729          | 0.74     | 0.7346 |
| 0.2421        | 4.0   | 340  | 0.9271          | 0.65     | 0.6591 |
| 0.177         | 5.0   | 425  | 1.0259          | 0.71     | 0.7199 |
| 0.1242        | 6.0   | 510  | 1.2122          | 0.68     | 0.6905 |
| 0.093         | 7.0   | 595  | 1.2365          | 0.68     | 0.6889 |
| 0.0886        | 8.0   | 680  | 1.2218          | 0.71     | 0.7185 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3