---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBertLexical-finetuned_70KURL
  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. -->

# PhoBertLexical-finetuned_70KURL

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1508
- Accuracy: 0.9565
- F1: 0.9565

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2150
- num_epochs: 20

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.4651 | 200  | 0.4128          | 0.8255   | 0.7984 |
| No log        | 0.9302 | 400  | 0.2414          | 0.9038   | 0.9057 |
| No log        | 1.3953 | 600  | 0.1894          | 0.9289   | 0.9294 |
| No log        | 1.8605 | 800  | 0.1859          | 0.9293   | 0.9307 |
| 0.3236        | 2.3256 | 1000 | 0.1580          | 0.9423   | 0.9430 |
| 0.3236        | 2.7907 | 1200 | 0.1532          | 0.9405   | 0.9413 |
| 0.3236        | 3.2558 | 1400 | 0.1412          | 0.9478   | 0.9483 |
| 0.3236        | 3.7209 | 1600 | 0.1345          | 0.9514   | 0.9517 |
| 0.1539        | 4.1860 | 1800 | 0.1399          | 0.9498   | 0.9505 |
| 0.1539        | 4.6512 | 2000 | 0.1382          | 0.9504   | 0.9511 |
| 0.1539        | 5.1163 | 2200 | 0.1457          | 0.9492   | 0.9499 |
| 0.1539        | 5.5814 | 2400 | 0.1343          | 0.9543   | 0.9543 |
| 0.1146        | 6.0465 | 2600 | 0.1382          | 0.9573   | 0.9576 |
| 0.1146        | 6.5116 | 2800 | 0.1483          | 0.9518   | 0.9524 |
| 0.1146        | 6.9767 | 3000 | 0.1392          | 0.9501   | 0.9508 |
| 0.1146        | 7.4419 | 3200 | 0.1388          | 0.9500   | 0.9507 |
| 0.1146        | 7.9070 | 3400 | 0.1508          | 0.9565   | 0.9565 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1