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# urinary_carcinoma_classifier

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 145167345715929860710353977110167552.0000
- Accuracy: 0.5

## 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:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss                           | Accuracy |
|:-------------:|:-----:|:----:|:-----------------------------------------:|:--------:|
| No log        | 1.0   | 1    | 171619846545786152085242447388475392.0000 | 0.5      |
| No log        | 2.0   | 2    | 216416222105935722637923733961965568.0000 | 0.75     |
| No log        | 3.0   | 3    | 145167345715929860710353977110167552.0000 | 0.5      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1

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