---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1_v2
  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_v2

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: 0.0077

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.98  | 48   | 1.0151          |
| No log        | 1.96  | 96   | 0.5423          |
| No log        | 2.94  | 144  | 0.3287          |
| No log        | 3.92  | 192  | 0.2296          |
| No log        | 4.9   | 240  | 0.1795          |
| No log        | 5.88  | 288  | 0.1419          |
| No log        | 6.86  | 336  | 0.1083          |
| No log        | 7.84  | 384  | 0.0807          |
| No log        | 8.82  | 432  | 0.0609          |
| No log        | 9.8   | 480  | 0.0614          |
| 0.3965        | 10.78 | 528  | 0.0349          |
| 0.3965        | 11.76 | 576  | 0.0289          |
| 0.3965        | 12.73 | 624  | 0.0252          |
| 0.3965        | 13.71 | 672  | 0.0193          |
| 0.3965        | 14.69 | 720  | 0.0163          |
| 0.3965        | 15.67 | 768  | 0.0147          |
| 0.3965        | 16.65 | 816  | 0.0139          |
| 0.3965        | 17.63 | 864  | 0.0134          |
| 0.3965        | 18.61 | 912  | 0.0114          |
| 0.3965        | 19.59 | 960  | 0.0100          |
| 0.0339        | 20.57 | 1008 | 0.0083          |
| 0.0339        | 21.55 | 1056 | 0.0079          |
| 0.0339        | 22.53 | 1104 | 0.0077          |
| 0.0339        | 23.51 | 1152 | 0.0081          |
| 0.0339        | 24.49 | 1200 | 0.0077          |


### Framework versions

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