metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phobert-v2-finetune-hatespeech-kaggle
results: []
phobert-v2-finetune-hatespeech-kaggle
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7815
- Accuracy: 0.8713
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: 1e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2035 | 1.0 | 2678 | 0.4716 | 0.8707 |
| 0.2372 | 2.0 | 5356 | 0.4366 | 0.8744 |
| 0.1986 | 3.0 | 8034 | 0.4618 | 0.8681 |
| 0.175 | 4.0 | 10712 | 0.5475 | 0.8749 |
| 0.1533 | 5.0 | 13390 | 0.6177 | 0.8720 |
| 0.1213 | 6.0 | 16068 | 0.6154 | 0.8735 |
| 0.1171 | 7.0 | 18746 | 0.6709 | 0.8739 |
| 0.096 | 8.0 | 21424 | 0.7336 | 0.8724 |
| 0.078 | 9.0 | 24102 | 0.7496 | 0.8688 |
| 0.0832 | 10.0 | 26780 | 0.7815 | 0.8713 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3