---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: phobert-base-v2-ed
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# phobert-base-v2-ed

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: 0.0541
- F1 Micro: 0.7087
- F1 Macro: 0.0259
- Recall Micro: 0.5880
- Precision Micro: 0.8918
- Recall Macro: 0.0257
- Precision Macro: 0.0262

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Recall Micro | Precision Micro | Recall Macro | Precision Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|:------------:|:---------------:|
| 0.069         | 1.0   | 1526 | 0.0706          | 0.6892   | 0.0243   | 0.6737       | 0.7054          | 0.0294       | 0.0207          |
| 0.0512        | 2.0   | 3052 | 0.0636          | 0.7055   | 0.0255   | 0.6165       | 0.8245          | 0.0269       | 0.0243          |
| 0.0629        | 3.0   | 4578 | 0.0577          | 0.7013   | 0.0257   | 0.5812       | 0.8840          | 0.0254       | 0.0260          |
| 0.0574        | 4.0   | 6104 | 0.0550          | 0.7120   | 0.0259   | 0.6024       | 0.8706          | 0.0263       | 0.0256          |
| 0.0375        | 5.0   | 7630 | 0.0541          | 0.7087   | 0.0259   | 0.5880       | 0.8918          | 0.0257       | 0.0262          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1