|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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](https://huggingface.co/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 |
|
|
