
<!-- 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. -->

# phobert-base-v2-finetuned-cola

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: 0.4604
- Accuracy: 0.9018
- F1: 0.9034
- Precision: 0.9080
- Recall: 0.9018

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 39   | 1.1866          | 0.8474   | 0.8536 | 0.8922    | 0.8474 |
| No log        | 2.0   | 78   | 0.8260          | 0.8632   | 0.8683 | 0.8967    | 0.8632 |
| No log        | 3.0   | 117  | 0.4604          | 0.9018   | 0.9034 | 0.9080    | 0.9018 |
| No log        | 4.0   | 156  | 0.6405          | 0.8912   | 0.8927 | 0.8962    | 0.8912 |
| No log        | 5.0   | 195  | 0.6415          | 0.8895   | 0.8909 | 0.8941    | 0.8895 |
| No log        | 6.0   | 234  | 0.6742          | 0.9053   | 0.9074 | 0.9157    | 0.9053 |
| No log        | 7.0   | 273  | 0.8472          | 0.8719   | 0.8762 | 0.8971    | 0.8719 |
| No log        | 8.0   | 312  | 0.7390          | 0.8947   | 0.8975 | 0.9086    | 0.8947 |
| No log        | 9.0   | 351  | 0.7700          | 0.8930   | 0.8958 | 0.9074    | 0.8930 |
| No log        | 10.0  | 390  | 0.7635          | 0.8930   | 0.8958 | 0.9074    | 0.8930 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "vinai/phobert-base-v2", "model-index": [{"name": "phobert-base-v2-finetuned-cola", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:vinai/phobert-base-v2 autotrain_compatible endpoints_compatible region:us