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
results: []
beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled
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: 0.0487
- Accuracy: 0.9893
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 |
|---|---|---|---|---|
| 2.1055 | 1.0 | 114 | 2.0091 | 0.1601 |
| 1.6582 | 2.0 | 229 | 1.5953 | 0.4187 |
| 1.2399 | 3.0 | 343 | 1.1053 | 0.5977 |
| 0.8417 | 4.0 | 458 | 0.7602 | 0.7241 |
| 0.5517 | 5.0 | 572 | 0.5651 | 0.8013 |
| 0.5777 | 6.0 | 687 | 0.3980 | 0.8768 |
| 0.408 | 7.0 | 801 | 0.2912 | 0.9154 |
| 0.2395 | 8.0 | 916 | 0.2185 | 0.9417 |
| 0.3613 | 9.0 | 1030 | 0.1753 | 0.9475 |
| 0.2408 | 10.0 | 1145 | 0.1353 | 0.9614 |
| 0.2777 | 11.0 | 1259 | 0.0699 | 0.9860 |
| 0.1528 | 11.95 | 1368 | 0.0487 | 0.9893 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3