metadata
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: project-2-training-top
results: []
project-2-training-top
This model is a fine-tuned version of vinai/phobert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3225
- F1: 0.6026
- Roc Auc: 0.7302
- Accuracy: 0.4977
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3397 | 1.0 | 73895 | 0.3244 | 0.5931 | 0.7238 | 0.4826 |
| 0.337 | 2.0 | 147790 | 0.3232 | 0.5987 | 0.7277 | 0.4925 |
| 0.3448 | 3.0 | 221685 | 0.3225 | 0.6026 | 0.7302 | 0.4977 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2