---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_w2v-1
  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-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: 1.4343
- Accuracy: 0.68
- F1: 0.6880

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8759        | 1.0   | 85   | 0.7015          | 0.69     | 0.6757 |
| 0.5289        | 2.0   | 170  | 0.6832          | 0.73     | 0.7309 |
| 0.3305        | 3.0   | 255  | 0.7459          | 0.68     | 0.6874 |
| 0.2115        | 4.0   | 340  | 0.9393          | 0.71     | 0.7102 |
| 0.1307        | 5.0   | 425  | 1.1584          | 0.68     | 0.6905 |
| 0.0937        | 6.0   | 510  | 1.2802          | 0.67     | 0.6791 |
| 0.0892        | 7.0   | 595  | 1.3824          | 0.69     | 0.6985 |
| 0.0719        | 8.0   | 680  | 1.4343          | 0.68     | 0.6880 |


### Framework versions

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