---
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBert_Lexical_Hosting_Dataset10K
  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. -->

# PhoBert_Lexical_Hosting_Dataset10K

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: 0.4273
- Accuracy: 0.8794
- F1: 0.8974

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 1.7448        | 1.2422  | 200  | 0.5205          | 0.7188   | 0.7907 |
| 1.7737        | 2.4845  | 400  | 0.3096          | 0.9020   | 0.9067 |
| 1.3408        | 3.7267  | 600  | 0.3578          | 0.8771   | 0.8938 |
| 1.7858        | 4.9689  | 800  | 0.3340          | 0.8927   | 0.9039 |
| 1.1154        | 6.2112  | 1000 | 0.2603          | 0.9155   | 0.9179 |
| 1.2382        | 7.4534  | 1200 | 0.4342          | 0.8434   | 0.8738 |
| 1.1267        | 8.6957  | 1400 | 0.3936          | 0.8697   | 0.8904 |
| 1.0833        | 9.9379  | 1600 | 0.3876          | 0.8677   | 0.8892 |
| 1.1027        | 11.1801 | 1800 | 0.4320          | 0.8757   | 0.8948 |
| 0.8329        | 12.4224 | 2000 | 0.3797          | 0.8832   | 0.8995 |
| 1.1287        | 13.6646 | 2200 | 0.4414          | 0.8677   | 0.8900 |
| 1.1326        | 14.9068 | 2400 | 0.4273          | 0.8794   | 0.8974 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.20.3