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---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_keras_callback
model-index:
- name: SaladSlayer00/image_classification_resnet
  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. -->

# SaladSlayer00/image_classification_resnet

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.0071
- Validation Loss: 2.8524
- Validation Accuracy: 0.3012
- Epoch: 5

## 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': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:---------------:|:-------------------:|:-----:|
| 7.0750     | 4.8746          | 0.0090              | 0     |
| 4.6468     | 4.5229          | 0.0538              | 1     |
| 4.3211     | 4.1033          | 0.1209              | 2     |
| 3.8784     | 3.6736          | 0.1859              | 3     |
| 3.4274     | 3.2193          | 0.2419              | 4     |
| 3.0071     | 2.8524          | 0.3012              | 5     |


### Framework versions

- Transformers 4.36.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0