---
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: test
  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. -->

# test

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: 0.6816
- Accuracy: 0.8543
- F1: 0.8351

## 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
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.4545 | 150  | 0.6440          | 0.8190   | 0.6792 |
| No log        | 0.9091 | 300  | 0.5366          | 0.8283   | 0.7146 |
| 0.8169        | 1.3636 | 450  | 0.4794          | 0.8418   | 0.7297 |
| 0.8169        | 1.8182 | 600  | 0.4390          | 0.8608   | 0.8331 |
| 0.4454        | 2.2727 | 750  | 0.4754          | 0.8471   | 0.8247 |
| 0.4454        | 2.7273 | 900  | 0.4398          | 0.8564   | 0.8243 |
| 0.3148        | 3.1818 | 1050 | 0.4512          | 0.8553   | 0.8265 |
| 0.3148        | 3.6364 | 1200 | 0.4722          | 0.8519   | 0.8332 |
| 0.2367        | 4.0909 | 1350 | 0.4722          | 0.8596   | 0.8287 |
| 0.2367        | 4.5455 | 1500 | 0.4794          | 0.8623   | 0.8415 |
| 0.1722        | 5.0    | 1650 | 0.4721          | 0.8568   | 0.8257 |
| 0.1722        | 5.4545 | 1800 | 0.5492          | 0.8581   | 0.8293 |
| 0.1722        | 5.9091 | 1950 | 0.5362          | 0.8598   | 0.8285 |
| 0.1339        | 6.3636 | 2100 | 0.5936          | 0.8530   | 0.8311 |
| 0.1339        | 6.8182 | 2250 | 0.5909          | 0.8598   | 0.8284 |
| 0.1051        | 7.2727 | 2400 | 0.5739          | 0.8583   | 0.8358 |
| 0.1051        | 7.7273 | 2550 | 0.6112          | 0.8589   | 0.8348 |
| 0.0882        | 8.1818 | 2700 | 0.6568          | 0.8541   | 0.8304 |
| 0.0882        | 8.6364 | 2850 | 0.6647          | 0.8564   | 0.8373 |
| 0.0715        | 9.0909 | 3000 | 0.6697          | 0.8560   | 0.8363 |
| 0.0715        | 9.5455 | 3150 | 0.6750          | 0.8549   | 0.8386 |
| 0.0586        | 10.0   | 3300 | 0.6816          | 0.8543   | 0.8351 |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.22.1