---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: cls_comment-phobert-base-v2-v1.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cls_comment-phobert-base-v2-v1.0

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2202
- Accuracy: 0.9181
- F1 Score: 0.8517
- Recall: 0.8617
- Precision: 0.8419

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.2545        | 1.0   | 234  | 0.2509          | 0.8981   | 0.8068   | 0.7796 | 0.8360    |
| 0.208         | 2.0   | 469  | 0.2259          | 0.9098   | 0.8399   | 0.8666 | 0.8148    |
| 0.1675        | 2.99  | 702  | 0.2202          | 0.9181   | 0.8517   | 0.8617 | 0.8419    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2