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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-beans
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-beans
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 ahishamm/HAM_db_enhanced_balanced_reduced_50_20_20_50 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5305
- Accuracy: 0.8451
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0791 | 0.2304 | 100 | 1.0348 | 0.6335 |
| 0.9415 | 0.4608 | 200 | 0.9576 | 0.6449 |
| 0.7839 | 0.6912 | 300 | 0.8963 | 0.6662 |
| 0.7181 | 0.9217 | 400 | 0.8479 | 0.6963 |
| 0.3995 | 1.1521 | 500 | 0.7821 | 0.7170 |
| 0.5025 | 1.3825 | 600 | 0.6300 | 0.7837 |
| 0.4985 | 1.6129 | 700 | 0.7059 | 0.7490 |
| 0.4388 | 1.8433 | 800 | 0.5893 | 0.7857 |
| 0.2389 | 2.0737 | 900 | 0.5929 | 0.8077 |
| 0.2767 | 2.3041 | 1000 | 0.5795 | 0.8091 |
| 0.2387 | 2.5346 | 1100 | 0.6100 | 0.8091 |
| 0.1691 | 2.7650 | 1200 | 0.6175 | 0.8071 |
| 0.1738 | 2.9954 | 1300 | 0.5877 | 0.8198 |
| 0.0397 | 3.2258 | 1400 | 0.5766 | 0.8358 |
| 0.03 | 3.4562 | 1500 | 0.5681 | 0.8371 |
| 0.092 | 3.6866 | 1600 | 0.5305 | 0.8451 |
| 0.0416 | 3.9171 | 1700 | 0.5443 | 0.8471 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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