metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-train-aug_backtranslation
results: []
PhoBERT-train-aug_backtranslation
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1713
- Accuracy: 0.69
- F1: 0.6970
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8557 | 1.0 | 86 | 0.7842 | 0.7 | 0.6993 |
| 0.5489 | 2.0 | 172 | 0.6702 | 0.74 | 0.7413 |
| 0.3877 | 3.0 | 258 | 0.8122 | 0.68 | 0.6807 |
| 0.2813 | 4.0 | 344 | 0.8146 | 0.73 | 0.7413 |
| 0.1919 | 5.0 | 430 | 0.9890 | 0.71 | 0.7218 |
| 0.1669 | 6.0 | 516 | 1.0436 | 0.68 | 0.6876 |
| 0.1423 | 7.0 | 602 | 1.1447 | 0.69 | 0.6976 |
| 0.103 | 8.0 | 688 | 1.1713 | 0.69 | 0.6970 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3