metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: >-
beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd
results: []
beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0488
- Accuracy: 0.9901
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9835 | 1.0 | 114 | 1.9296 | 0.2315 |
| 1.6045 | 2.0 | 229 | 1.4334 | 0.5172 |
| 1.0525 | 3.0 | 343 | 0.9298 | 0.6962 |
| 0.795 | 4.0 | 458 | 0.6580 | 0.7709 |
| 0.5739 | 5.0 | 572 | 0.4717 | 0.8366 |
| 0.5821 | 6.0 | 687 | 0.3511 | 0.8851 |
| 0.4566 | 7.0 | 801 | 0.2705 | 0.9204 |
| 0.2751 | 8.0 | 916 | 0.2114 | 0.9384 |
| 0.2352 | 9.0 | 1030 | 0.1303 | 0.9688 |
| 0.1831 | 10.0 | 1145 | 0.1194 | 0.9688 |
| 0.1515 | 11.0 | 1259 | 0.0673 | 0.9869 |
| 0.204 | 11.95 | 1368 | 0.0488 | 0.9901 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3