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# vi-fin-news

This model is a fine-tuned version of [FPTAI/vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4509
- Accuracy: 0.9136

## 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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1176        | 1.0   | 1150 | 0.3566          | 0.9181   |
| 0.0582        | 2.0   | 2300 | 0.4509          | 0.9136   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3
{"language": ["vi"], "license": "apache-2.0", "library_name": "transformers", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "FPTAI/vibert-base-cased", "pipeline_tag": "text-classification", "model-index": [{"name": "vi-fin-news", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer vi base_model:FPTAI/vibert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us