metadata
library_name: transformers
base_model: Mardiyyah/biomedbert_model_extended_untrained
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cellate-tapt_base-LR_2e-05
results: []
cellate-tapt_base-LR_2e-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: 4.9618
- Accuracy: 0.3431
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: 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: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 10.1666 | 1.0 | 6 | 11.0374 | 0.0 |
| 9.6209 | 2.0 | 12 | 9.6987 | 0.0 |
| 8.2654 | 3.0 | 18 | 8.4261 | 0.0281 |
| 7.3452 | 4.0 | 24 | 7.7401 | 0.0637 |
| 6.7638 | 5.0 | 30 | 7.0736 | 0.1537 |
| 6.2231 | 6.0 | 36 | 6.6987 | 0.1956 |
| 5.7561 | 7.0 | 42 | 6.2060 | 0.2480 |
| 5.4166 | 8.0 | 48 | 5.9637 | 0.2752 |
| 5.1312 | 9.0 | 54 | 5.7060 | 0.2832 |
| 4.9182 | 10.0 | 60 | 5.5990 | 0.2995 |
| 4.6794 | 11.0 | 66 | 5.3070 | 0.3117 |
| 4.5745 | 12.0 | 72 | 5.2026 | 0.3180 |
| 4.4439 | 13.0 | 78 | 5.0539 | 0.3331 |
| 4.412 | 14.0 | 84 | 5.0538 | 0.3469 |
| 4.2761 | 15.0 | 90 | 5.2681 | 0.3167 |
| 4.3235 | 16.0 | 96 | 4.9841 | 0.3259 |
| 4.5983 | 16.7273 | 100 | 4.9618 | 0.3431 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0