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# resnet-pretrained-brain-mri

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the BrainMRI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1450
- Accuracy: 0.5228

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 72   | 0.4704   | 1.2440          |
| 1.2771        | 2.0   | 144  | 0.5575   | 1.1610          |
| 1.1543        | 3.0   | 216  | 0.6446   | 1.0949          |
| 1.1543        | 4.0   | 288  | 0.6812   | 1.0361          |
| 1.0664        | 5.0   | 360  | 0.6742   | 1.0100          |
| 0.9998        | 6.0   | 432  | 0.7003   | 0.9687          |
| 0.9537        | 7.0   | 504  | 0.6986   | 0.9484          |
| 0.9537        | 8.0   | 576  | 0.6934   | 0.9285          |
| 0.9239        | 9.0   | 648  | 0.7108   | 0.8992          |
| 0.893         | 10.0  | 720  | 0.7369   | 0.8723          |
| 0.893         | 11.0  | 792  | 0.7334   | 0.8635          |
| 0.8726        | 12.0  | 864  | 0.7474   | 0.8589          |
| 0.8482        | 13.0  | 936  | 0.7160   | 0.8423          |
| 0.8461        | 14.0  | 1008 | 0.7300   | 0.8481          |
| 0.8461        | 15.0  | 1080 | 0.7352   | 0.8312          |
| 0.8267        | 16.0  | 1152 | 0.7247   | 0.8319          |
| 0.8163        | 17.0  | 1224 | 0.7456   | 0.8136          |
| 0.8163        | 18.0  | 1296 | 0.7474   | 0.8151          |
| 0.8126        | 19.0  | 1368 | 0.7596   | 0.8071          |
| 0.8022        | 20.0  | 1440 | 0.7491   | 0.8210          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1

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