---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1_v4
  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_v4

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: 0.0046

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.98  | 48   | 1.0265          |
| No log        | 1.96  | 96   | 0.5809          |
| No log        | 2.94  | 144  | 0.3461          |
| No log        | 3.92  | 192  | 0.2725          |
| No log        | 4.9   | 240  | 0.2168          |
| No log        | 5.88  | 288  | 0.1728          |
| No log        | 6.86  | 336  | 0.1516          |
| No log        | 7.84  | 384  | 0.1076          |
| No log        | 8.82  | 432  | 0.0783          |
| No log        | 9.8   | 480  | 0.0653          |
| 0.4162        | 10.78 | 528  | 0.0473          |
| 0.4162        | 11.76 | 576  | 0.0413          |
| 0.4162        | 12.73 | 624  | 0.0344          |
| 0.4162        | 13.71 | 672  | 0.0253          |
| 0.4162        | 14.69 | 720  | 0.0244          |
| 0.4162        | 15.67 | 768  | 0.0204          |
| 0.4162        | 16.65 | 816  | 0.0210          |
| 0.4162        | 17.63 | 864  | 0.0168          |
| 0.4162        | 18.61 | 912  | 0.0155          |
| 0.4162        | 19.59 | 960  | 0.0132          |
| 0.0375        | 20.57 | 1008 | 0.0130          |
| 0.0375        | 21.55 | 1056 | 0.0097          |
| 0.0375        | 22.53 | 1104 | 0.0088          |
| 0.0375        | 23.51 | 1152 | 0.0081          |
| 0.0375        | 24.49 | 1200 | 0.0080          |
| 0.0375        | 25.47 | 1248 | 0.0069          |
| 0.0375        | 26.45 | 1296 | 0.0065          |
| 0.0375        | 27.43 | 1344 | 0.0062          |
| 0.0375        | 28.41 | 1392 | 0.0060          |
| 0.0375        | 29.39 | 1440 | 0.0056          |
| 0.0375        | 30.37 | 1488 | 0.0055          |
| 0.0114        | 31.35 | 1536 | 0.0053          |
| 0.0114        | 32.33 | 1584 | 0.0052          |
| 0.0114        | 33.31 | 1632 | 0.0051          |
| 0.0114        | 34.29 | 1680 | 0.0049          |
| 0.0114        | 35.27 | 1728 | 0.0048          |
| 0.0114        | 36.24 | 1776 | 0.0048          |
| 0.0114        | 37.22 | 1824 | 0.0047          |
| 0.0114        | 38.2  | 1872 | 0.0047          |
| 0.0114        | 39.18 | 1920 | 0.0046          |


### Framework versions

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