---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: project-2
  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. -->

# project-2

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: 0.2549
- F1: 0.7177
- Roc Auc: 0.8111
- Accuracy: 0.6724

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step   | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|:--------:|
| 0.2526        | 1.0   | 73895  | 0.2578          | 0.7127 | 0.8065  | 0.6596   |
| 0.2367        | 2.0   | 147790 | 0.2549          | 0.7177 | 0.8111  | 0.6724   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2