variant-tapt_freeze_llrd_ww_mask-LR_5e-05
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on the Mardiyyah/TAPT_Variant_FT dataset. It achieves the following results on the evaluation set:
- Loss: 1.4054
- Accuracy: 0.7228
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: 0.06
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6473 | 1.0 | 19 | 1.6487 | 0.6997 |
| 1.6283 | 2.0 | 38 | 1.6091 | 0.7057 |
| 1.5706 | 3.0 | 57 | 1.5814 | 0.7040 |
| 1.5255 | 4.0 | 76 | 1.5358 | 0.7120 |
| 1.5047 | 5.0 | 95 | 1.5496 | 0.7085 |
| 1.4924 | 6.0 | 114 | 1.4409 | 0.7167 |
| 1.463 | 7.0 | 133 | 1.4329 | 0.7179 |
| 1.4172 | 8.0 | 152 | 1.5335 | 0.7107 |
| 1.4397 | 9.0 | 171 | 1.4242 | 0.7189 |
| 1.4296 | 10.0 | 190 | 1.4802 | 0.7081 |
| 1.399 | 11.0 | 209 | 1.4528 | 0.7215 |
| 1.4182 | 12.0 | 228 | 1.4391 | 0.7149 |
| 1.4079 | 13.0 | 247 | 1.4564 | 0.7185 |
| 1.4032 | 14.0 | 266 | 1.4057 | 0.7202 |
| 1.4094 | 15.0 | 285 | 1.4528 | 0.7146 |
| 1.3706 | 16.0 | 304 | 1.4888 | 0.7160 |
| 1.3522 | 17.0 | 323 | 1.4005 | 0.7207 |
| 1.3732 | 18.0 | 342 | 1.4291 | 0.7118 |
| 1.3696 | 19.0 | 361 | 1.4123 | 0.7221 |
| 1.3729 | 20.0 | 380 | 1.4188 | 0.7199 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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