metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: cls_comment-phobert-base-v2-v1.0
results: []
cls_comment-phobert-base-v2-v1.0
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: 0.2202
- Accuracy: 0.9181
- F1 Score: 0.8517
- Recall: 0.8617
- Precision: 0.8419
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.2545 | 1.0 | 234 | 0.2509 | 0.8981 | 0.8068 | 0.7796 | 0.8360 |
| 0.208 | 2.0 | 469 | 0.2259 | 0.9098 | 0.8399 | 0.8666 | 0.8148 |
| 0.1675 | 2.99 | 702 | 0.2202 | 0.9181 | 0.8517 | 0.8617 | 0.8419 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2