metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: phobert-student-distilled
results: []
phobert-student-distilled
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0268
- Precision: 0.9399
- Recall: 0.9553
- F1: 0.9475
- Accuracy: 0.9914
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0486 | 1.0 | 1683 | 0.0387 | 0.8994 | 0.9339 | 0.9164 | 0.9877 |
| 0.0315 | 2.0 | 3366 | 0.0320 | 0.9277 | 0.9474 | 0.9374 | 0.9904 |
| 0.0260 | 3.0 | 5049 | 0.0294 | 0.9351 | 0.9523 | 0.9436 | 0.9905 |
| 0.0188 | 4.0 | 6732 | 0.0268 | 0.9417 | 0.9550 | 0.9483 | 0.9919 |
| 0.0186 | 5.0 | 8415 | 0.0268 | 0.9399 | 0.9553 | 0.9475 | 0.9914 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2