---
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phobert-base_v3
  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-base_v3

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2798
- Accuracy: 0.7805
- Precision Macro: 0.7813
- Recall Macro: 0.7807
- F1 Macro: 0.7806
- F1 Weighted: 0.7806

## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
| 1.0861        | 1.0   | 72   | 0.8945          | 0.5863   | 0.6024          | 0.5883       | 0.5734   | 0.5725      |
| 0.8854        | 2.0   | 144  | 0.7401          | 0.6993   | 0.7354          | 0.6992       | 0.6982   | 0.6983      |
| 0.5405        | 3.0   | 216  | 0.5891          | 0.7814   | 0.7817          | 0.7816       | 0.7813   | 0.7813      |
| 0.4119        | 4.0   | 288  | 0.6523          | 0.7761   | 0.7776          | 0.7758       | 0.7760   | 0.7760      |
| 0.2355        | 5.0   | 360  | 0.6712          | 0.7894   | 0.7899          | 0.7892       | 0.7894   | 0.7894      |
| 0.1786        | 6.0   | 432  | 0.8116          | 0.7725   | 0.7733          | 0.7726       | 0.7726   | 0.7726      |
| 0.1126        | 7.0   | 504  | 0.8907          | 0.7761   | 0.7792          | 0.7761       | 0.7761   | 0.7761      |
| 0.0844        | 8.0   | 576  | 0.9184          | 0.7827   | 0.7834          | 0.7825       | 0.7826   | 0.7827      |
| 0.0657        | 9.0   | 648  | 1.0276          | 0.7734   | 0.7769          | 0.7735       | 0.7737   | 0.7737      |
| 0.0458        | 10.0  | 720  | 1.2265          | 0.7583   | 0.7713          | 0.7581       | 0.7582   | 0.7583      |
| 0.0494        | 11.0  | 792  | 1.1001          | 0.7783   | 0.7793          | 0.7783       | 0.7784   | 0.7784      |
| 0.0307        | 12.0  | 864  | 1.1487          | 0.7783   | 0.7798          | 0.7781       | 0.7783   | 0.7783      |
| 0.0284        | 13.0  | 936  | 1.1877          | 0.7805   | 0.7812          | 0.7805       | 0.7805   | 0.7805      |
| 0.0192        | 14.0  | 1008 | 1.2280          | 0.7836   | 0.7843          | 0.7839       | 0.7836   | 0.7836      |
| 0.0172        | 15.0  | 1080 | 1.2466          | 0.7823   | 0.7823          | 0.7823       | 0.7823   | 0.7823      |
| 0.0108        | 16.0  | 1152 | 1.2673          | 0.7809   | 0.7837          | 0.7810       | 0.7812   | 0.7812      |
| 0.0111        | 17.0  | 1224 | 1.2614          | 0.7823   | 0.7825          | 0.7823       | 0.7823   | 0.7823      |
| 0.0094        | 18.0  | 1296 | 1.2754          | 0.7814   | 0.7817          | 0.7815       | 0.7814   | 0.7815      |
| 0.0079        | 19.0  | 1368 | 1.2823          | 0.7809   | 0.7821          | 0.7811       | 0.7811   | 0.7811      |
| 0.0095        | 20.0  | 1440 | 1.2798          | 0.7805   | 0.7813          | 0.7807       | 0.7806   | 0.7806      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4