transformers tf vit image-classification generated_from_keras_callback base_model:anum231/cancer_classifier_100 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: anum231/cancer_classifier_100
tags:
- generated_from_keras_callback
model-index:
- name: anum231/cancer_classifier_100
  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. -->

# anum231/cancer_classifier_100

This model is a fine-tuned version of [anum231/cancer_classifier_100](https://huggingface.co/anum231/cancer_classifier_100) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5354
- Validation Loss: 0.8077
- Train Accuracy: 0.6724
- Epoch: 22

## 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': 4640, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.0644     | 0.9210          | 0.5690         | 0     |
| 0.8927     | 0.8785          | 0.5345         | 1     |
| 0.8065     | 0.9131          | 0.6379         | 2     |
| 0.7085     | 0.7569          | 0.7241         | 3     |
| 0.7407     | 0.7963          | 0.6897         | 4     |
| 0.6635     | 0.8031          | 0.6897         | 5     |
| 0.7505     | 0.8074          | 0.6552         | 6     |
| 0.6149     | 0.8540          | 0.6379         | 7     |
| 0.6530     | 0.7823          | 0.6379         | 8     |
| 0.5969     | 0.8384          | 0.6552         | 9     |
| 0.6808     | 0.7863          | 0.6552         | 10    |
| 0.6269     | 0.8650          | 0.6552         | 11    |
| 0.5665     | 0.7941          | 0.6897         | 12    |
| 0.6414     | 0.8927          | 0.6552         | 13    |
| 0.7304     | 0.9703          | 0.6034         | 14    |
| 0.5518     | 0.9204          | 0.6552         | 15    |
| 0.6184     | 0.8850          | 0.6897         | 16    |
| 0.6397     | 0.8827          | 0.6724         | 17    |
| 0.5697     | 0.8658          | 0.6207         | 18    |
| 0.6103     | 0.8177          | 0.6379         | 19    |
| 0.5541     | 0.8526          | 0.6552         | 20    |
| 0.5831     | 0.8632          | 0.6379         | 21    |
| 0.5354     | 0.8077          | 0.6724         | 22    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1
