CeLLaTe-tapt-bioformer16l-tokenizer-adapted-baseline
This model is a fine-tuned version of bioformers/bioformer-16l on the Mardiyyah/TAPT_CeLLaTe2.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3768
- Accuracy: 0.7284
- Perplexity: 3.9623
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: 32
- eval_batch_size: 32
- seed: 3407
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 0.06
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Perplexity |
|---|---|---|---|---|---|
| 1.9156 | 1.0 | 15 | 1.6188 | 0.7112 | 5.0472 |
| 1.8799 | 2.0 | 30 | 1.5831 | 0.7161 | 4.8702 |
| 1.8013 | 3.0 | 45 | 1.5291 | 0.7222 | 4.6141 |
| 1.7449 | 4.0 | 60 | 1.4859 | 0.7253 | 4.4191 |
| 1.7088 | 5.0 | 75 | 1.4696 | 0.7265 | 4.3475 |
| 1.6504 | 6.0 | 90 | 1.4740 | 0.7237 | 4.3665 |
| 1.6389 | 7.0 | 105 | 1.4179 | 0.7270 | 4.1284 |
| 1.5959 | 8.0 | 120 | 1.4521 | 0.7231 | 4.2721 |
| 1.5839 | 9.0 | 135 | 1.3957 | 0.7304 | 4.0378 |
| 1.5529 | 10.0 | 150 | 1.3926 | 0.7328 | 4.0254 |
| 1.5166 | 11.0 | 165 | 1.3766 | 0.7325 | 3.9613 |
| 1.5055 | 12.0 | 180 | 1.3351 | 0.7398 | 3.8003 |
| 1.4887 | 13.0 | 195 | 1.4013 | 0.7315 | 4.0604 |
| 1.4724 | 14.0 | 210 | 1.3644 | 0.7362 | 3.9134 |
| 1.4553 | 15.0 | 225 | 1.3633 | 0.7352 | 3.9093 |
| 1.4581 | 16.0 | 240 | 1.3672 | 0.7312 | 3.9245 |
| 1.4307 | 17.0 | 255 | 1.3518 | 0.7351 | 3.8645 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0