metadata
library_name: transformers
base_model: Mardiyyah/biomedbert_model_extended_untrained
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cellate-tapt_base-LR_5e-05
results: []
cellate-tapt_base-LR_5e-05
This model is a fine-tuned version of Mardiyyah/biomedbert_model_extended_untrained on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.0082
- Accuracy: 0.3427
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 3407
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 10.0856 | 1.0 | 6 | 9.3860 | 0.0013 |
| 7.7042 | 2.0 | 12 | 7.4853 | 0.0846 |
| 6.4607 | 3.0 | 18 | 6.6518 | 0.2061 |
| 5.6761 | 4.0 | 24 | 6.0114 | 0.2627 |
| 5.1206 | 5.0 | 30 | 5.5058 | 0.3000 |
| 4.6513 | 6.0 | 36 | 5.2675 | 0.3100 |
| 4.3594 | 7.0 | 42 | 5.0053 | 0.3368 |
| 4.2179 | 8.0 | 48 | 4.9603 | 0.3460 |
| 4.5052 | 8.3636 | 50 | 5.0082 | 0.3427 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0