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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-images
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. -->
# vit-base-images
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the marmal88/skin_cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0918
- Accuracy: 0.981
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8785 | 0.4 | 100 | 0.7795 | 0.711 |
| 0.7076 | 0.8 | 200 | 0.5421 | 0.818 |
| 0.4283 | 1.2 | 300 | 0.3951 | 0.876 |
| 0.4251 | 1.6 | 400 | 0.3818 | 0.864 |
| 0.335 | 2.0 | 500 | 0.2474 | 0.924 |
| 0.2286 | 2.4 | 600 | 0.1675 | 0.952 |
| 0.1523 | 2.8 | 700 | 0.1641 | 0.954 |
| 0.1346 | 3.2 | 800 | 0.1120 | 0.969 |
| 0.0638 | 3.6 | 900 | 0.1025 | 0.978 |
| 0.0574 | 4.0 | 1000 | 0.0918 | 0.981 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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