---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_w2v
  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. -->

# PhoBERT-Final_Mixed-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: 1.1056
- Accuracy: 0.73
- F1: 0.7280

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8961        | 1.0   | 86   | 0.7149          | 0.69     | 0.6676 |
| 0.5695        | 2.0   | 172  | 0.7188          | 0.71     | 0.7029 |
| 0.3772        | 3.0   | 258  | 0.7802          | 0.71     | 0.7061 |
| 0.2899        | 4.0   | 344  | 0.7639          | 0.76     | 0.7595 |
| 0.2145        | 5.0   | 430  | 0.9140          | 0.73     | 0.7286 |
| 0.1299        | 6.0   | 516  | 1.0655          | 0.72     | 0.7123 |
| 0.1047        | 7.0   | 602  | 1.0912          | 0.73     | 0.7244 |
| 0.0864        | 8.0   | 688  | 1.1056          | 0.73     | 0.7280 |


### Framework versions

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