Instructions to use DienQuocHuy/TextGraphFuseGAT-PhoNER-Covid19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DienQuocHuy/TextGraphFuseGAT-PhoNER-Covid19 with Transformers:
# Load model directly from transformers import TextGraphFuseGAT model = TextGraphFuseGAT.from_pretrained("DienQuocHuy/TextGraphFuseGAT-PhoNER-Covid19", dtype="auto") - Notebooks
- Google Colab
- Kaggle
TextGraphFuseGAT-PhoNER-Covid19
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2348
- Precision: 0.4887
- Recall: 0.2810
- F1: 0.3568
- Accuracy: 0.8054
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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 1.7504 | 0.2653 | 0.0017 | 0.0035 | 0.7490 |
| No log | 2.0 | 158 | 1.7017 | 0.0 | 0.0 | 0.0 | 0.7486 |
| No log | 3.0 | 237 | 1.6819 | 0.0 | 0.0 | 0.0 | 0.7493 |
| No log | 4.0 | 316 | 1.4227 | 0.6283 | 0.1598 | 0.2548 | 0.7835 |
| No log | 5.0 | 395 | 1.1841 | 0.4963 | 0.2854 | 0.3624 | 0.8123 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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