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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Wound-classification
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. -->
# Wound-classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1836
- Accuracy: 0.9575
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 16
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1241 | 1.0 | 200 | 0.7452 | 0.765 |
| 0.5854 | 2.0 | 400 | 0.4880 | 0.835 |
| 0.4279 | 3.0 | 600 | 0.5049 | 0.8375 |
| 0.4041 | 4.0 | 800 | 0.3321 | 0.8975 |
| 0.2805 | 5.0 | 1000 | 0.4105 | 0.895 |
| 0.279 | 6.0 | 1200 | 0.4269 | 0.8825 |
| 0.1782 | 7.0 | 1400 | 0.3583 | 0.905 |
| 0.1834 | 8.0 | 1600 | 0.3009 | 0.925 |
| 0.1197 | 9.0 | 1800 | 0.3020 | 0.93 |
| 0.1231 | 10.0 | 2000 | 0.3352 | 0.9225 |
| 0.1273 | 11.0 | 2200 | 0.2908 | 0.91 |
| 0.1019 | 12.0 | 2400 | 0.2528 | 0.94 |
| 0.0951 | 13.0 | 2600 | 0.2989 | 0.9325 |
| 0.0957 | 14.0 | 2800 | 0.3189 | 0.9325 |
| 0.0618 | 15.0 | 3000 | 0.1973 | 0.9475 |
| 0.0583 | 16.0 | 3200 | 0.1836 | 0.9575 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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