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

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: 0.3225
- F1: 0.6026
- Roc Auc: 0.7302
- Accuracy: 0.4977

## 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: 3

### Training results

| Training Loss | Epoch | Step   | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|:--------:|
| 0.3397        | 1.0   | 73895  | 0.3244          | 0.5931 | 0.7238  | 0.4826   |
| 0.337         | 2.0   | 147790 | 0.3232          | 0.5987 | 0.7277  | 0.4925   |
| 0.3448        | 3.0   | 221685 | 0.3225          | 0.6026 | 0.7302  | 0.4977   |


### Framework versions

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