---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_w2v-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# PhoBERT-Final_Mixed-aug_insert_w2v-2

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: 1.2182
- Accuracy: 0.69
- F1: 0.6910

## 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: 40
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9152        | 1.0   | 86   | 0.7599          | 0.68     | 0.6556 |
| 0.6043        | 2.0   | 172  | 0.7114          | 0.7      | 0.7023 |
| 0.4061        | 3.0   | 258  | 0.7314          | 0.73     | 0.7344 |
| 0.2797        | 4.0   | 344  | 0.9199          | 0.71     | 0.7051 |
| 0.183         | 5.0   | 430  | 1.0362          | 0.71     | 0.7083 |
| 0.1371        | 6.0   | 516  | 1.1032          | 0.71     | 0.7065 |
| 0.0894        | 7.0   | 602  | 1.1811          | 0.71     | 0.7101 |
| 0.0779        | 8.0   | 688  | 1.2182          | 0.69     | 0.6910 |


### Framework versions

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