metadata
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: >-
swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3
results: []
swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-Lesion-Classification-HAM10000-3
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0112
- Accuracy: 0.9951
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.5
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1885 | 1.0 | 114 | 0.8718 | 0.6593 |
| 0.7037 | 2.0 | 228 | 0.4208 | 0.8637 |
| 0.5085 | 2.99 | 342 | 0.3446 | 0.8744 |
| 0.2874 | 4.0 | 457 | 0.2027 | 0.9327 |
| 0.355 | 5.0 | 571 | 0.1666 | 0.9401 |
| 0.2493 | 6.0 | 685 | 0.0969 | 0.9655 |
| 0.1909 | 6.99 | 799 | 0.0558 | 0.9836 |
| 0.1821 | 8.0 | 914 | 0.0412 | 0.9901 |
| 0.1853 | 9.0 | 1028 | 0.0239 | 0.9943 |
| 0.0666 | 9.98 | 1140 | 0.0112 | 0.9951 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3