---
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Phobert_CITA_15k
  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_CITA_15k

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: 0.6995
- Accuracy: 0.8057
- F1: 0.8034

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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_with_restarts
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4825        | 1.0   | 375  | 0.4345          | 0.8047   | 0.7947 |
| 0.3984        | 2.0   | 750  | 0.4341          | 0.8033   | 0.8030 |
| 0.3466        | 3.0   | 1125 | 0.4692          | 0.8213   | 0.8158 |
| 0.3012        | 4.0   | 1500 | 0.5128          | 0.8147   | 0.8051 |
| 0.256         | 5.0   | 1875 | 0.5427          | 0.806    | 0.8061 |
| 0.213         | 6.0   | 2250 | 0.5851          | 0.8087   | 0.8022 |
| 0.1805        | 7.0   | 2625 | 0.6466          | 0.8083   | 0.8060 |
| 0.1568        | 8.0   | 3000 | 0.6883          | 0.81     | 0.8053 |
| 0.1453        | 9.0   | 3375 | 0.6956          | 0.8083   | 0.8056 |
| 0.1467        | 10.0  | 3750 | 0.6995          | 0.8057   | 0.8034 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.21.0