metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: phobert-base-v2-finetuned-cola
results: []
phobert-base-v2-finetuned-cola
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: 0.4604
- Accuracy: 0.9018
- F1: 0.9034
- Precision: 0.9080
- Recall: 0.9018
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
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 39 | 1.1866 | 0.8474 | 0.8536 | 0.8922 | 0.8474 |
| No log | 2.0 | 78 | 0.8260 | 0.8632 | 0.8683 | 0.8967 | 0.8632 |
| No log | 3.0 | 117 | 0.4604 | 0.9018 | 0.9034 | 0.9080 | 0.9018 |
| No log | 4.0 | 156 | 0.6405 | 0.8912 | 0.8927 | 0.8962 | 0.8912 |
| No log | 5.0 | 195 | 0.6415 | 0.8895 | 0.8909 | 0.8941 | 0.8895 |
| No log | 6.0 | 234 | 0.6742 | 0.9053 | 0.9074 | 0.9157 | 0.9053 |
| No log | 7.0 | 273 | 0.8472 | 0.8719 | 0.8762 | 0.8971 | 0.8719 |
| No log | 8.0 | 312 | 0.7390 | 0.8947 | 0.8975 | 0.9086 | 0.8947 |
| No log | 9.0 | 351 | 0.7700 | 0.8930 | 0.8958 | 0.9074 | 0.8930 |
| No log | 10.0 | 390 | 0.7635 | 0.8930 | 0.8958 | 0.9074 | 0.8930 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2