metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Wound-Image-classification
results: []
Wound-Image-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0475
- Accuracy: 0.7586
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8893 | 1.0 | 86 | 1.8192 | 0.4253 |
| 1.6679 | 2.0 | 172 | 1.5983 | 0.4828 |
| 1.4013 | 3.0 | 258 | 1.3888 | 0.6437 |
| 1.2347 | 4.0 | 344 | 1.2665 | 0.6782 |
| 1.0931 | 5.0 | 430 | 1.1818 | 0.6782 |
| 0.9913 | 6.0 | 516 | 1.1167 | 0.7241 |
| 0.9458 | 7.0 | 602 | 1.0819 | 0.7241 |
| 0.909 | 8.0 | 688 | 1.0475 | 0.7586 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2