---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1
  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. -->

# CS505-Classifier-T4_predictLabel_a1

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0155

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.98  | 48   | 1.0473          |
| No log        | 1.96  | 96   | 0.5664          |
| No log        | 2.94  | 144  | 0.3371          |
| No log        | 3.92  | 192  | 0.2277          |
| No log        | 4.9   | 240  | 0.1850          |
| No log        | 5.88  | 288  | 0.1451          |
| No log        | 6.86  | 336  | 0.1126          |
| No log        | 7.84  | 384  | 0.0853          |
| No log        | 8.82  | 432  | 0.0635          |
| No log        | 9.8   | 480  | 0.0598          |
| 0.4029        | 10.78 | 528  | 0.0407          |
| 0.4029        | 11.76 | 576  | 0.0337          |
| 0.4029        | 12.73 | 624  | 0.0300          |
| 0.4029        | 13.71 | 672  | 0.0270          |
| 0.4029        | 14.69 | 720  | 0.0209          |
| 0.4029        | 15.67 | 768  | 0.0196          |
| 0.4029        | 16.65 | 816  | 0.0205          |
| 0.4029        | 17.63 | 864  | 0.0181          |
| 0.4029        | 18.61 | 912  | 0.0160          |
| 0.4029        | 19.59 | 960  | 0.0155          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2