---
license: other
base_model: nvidia/mit-b1
tags:
- generated_from_keras_callback
model-index:
- name: ahmed-ai/mit-b1-skin-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# ahmed-ai/mit-b1-skin-classifier

<h2 style="color:red; font-size: 3rem">Important Warning</h2>  
<p style="font-weight: bold; font-size: 1.5rem;">This model is currently undergoing development; as such, it should not be used for clinical diagnosis or relied upon for medical decision-making at this stage.</p>

This model is a fine-tuned version of [nvidia/mit-b1](https://huggingface.co/nvidia/mit-b1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4567
- Validation Loss: 0.6271
- Train Accuracy: 0.7610
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 191770, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.1152     | 0.8715          | 0.6858         | 0     |
| 0.8784     | 0.7400          | 0.7216         | 1     |
| 0.7774     | 0.7492          | 0.7273         | 2     |
| 0.7114     | 0.7229          | 0.7213         | 3     |
| 0.6492     | 0.6735          | 0.7393         | 4     |
| 0.6005     | 0.6498          | 0.7507         | 5     |
| 0.5560     | 0.6181          | 0.7596         | 6     |
| 0.5179     | 0.6473          | 0.7582         | 7     |
| 0.4913     | 0.6100          | 0.7711         | 8     |
| 0.4567     | 0.6271          | 0.7610         | 9     |


### Framework versions

- Transformers 4.36.2
- TensorFlow 2.13.0
- Datasets 2.16.1
- Tokenizers 0.15.0