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drug-classifier
Haitam03/drug-classifier
drug-classifier is a text classification model from Haitam03. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Sep 29, 2025
- Updated
- Sep 29, 2025
- SHA
- 8252e0a6
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
drug-classifier
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6099
- Accuracy: 0.8120
- F1: 0.8037
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.5696 | 0.1492 | 500 | 1.4351 | 0.6050 | 0.5430 |
| 1.0091 | 0.2985 | 1000 | 0.9559 | 0.7178 | 0.6886 |
| 0.8572 | 0.4477 | 1500 | 0.8307 | 0.7450 | 0.7253 |
| 0.801 | 0.5970 | 2000 | 0.7775 | 0.7585 | 0.7422 |
| 0.7474 | 0.7462 | 2500 | 0.7413 | 0.7682 | 0.7525 |
| 0.6923 | 0.8955 | 3000 | 0.7179 | 0.7751 | 0.7643 |
| 0.6461 | 1.0445 | 3500 | 0.7038 | 0.7750 | 0.7643 |
| 0.6352 | 1.1937 | 4000 | 0.6927 | 0.7831 | 0.7697 |
| 0.6474 | 1.3430 | 4500 | 0.6766 | 0.7868 | 0.7750 |
| 0.5981 | 1.4922 | 5000 | 0.6601 | 0.7909 | 0.7800 |
| 0.5903 | 1.6414 | 5500 | 0.6669 | 0.7896 | 0.7802 |
| 0.6172 | 1.7907 | 6000 | 0.6364 | 0.7975 | 0.7869 |
| 0.6075 | 1.9399 | 6500 | 0.6318 | 0.7984 | 0.7884 |
| 0.4876 | 2.0889 | 7000 | 0.6348 | 0.7996 | 0.7920 |
| 0.5172 | 2.2382 | 7500 | 0.6311 | 0.8017 | 0.7943 |
| 0.5008 | 2.3874 | 8000 | 0.6216 | 0.8054 | 0.7972 |
| 0.4782 | 2.5367 | 8500 | 0.6181 | 0.8094 | 0.8016 |
| 0.506 | 2.6859 | 9000 | 0.6150 | 0.8095 | 0.8008 |
| 0.4969 | 2.8352 | 9500 | 0.6116 | 0.8093 | 0.8025 |
| 0.4844 | 2.9844 | 10000 | 0.6099 | 0.8120 | 0.8037 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 29, 2025
- Updated
- Sep 29, 2025