---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-brain-tumor
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9171249018067557
---

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

# resnet-50-finetuned-brain-tumor

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: 0.2757
- Accuracy: 0.9171

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.3264        | 1.0   | 30   | 0.5035   | 1.3154          |
| 1.222         | 2.0   | 60   | 0.6473   | 1.2254          |
| 1.0584        | 3.0   | 90   | 1.0668   | 0.7510          |
| 0.8977        | 4.0   | 120  | 0.9205   | 0.8060          |
| 0.724         | 5.0   | 150  | 0.7740   | 0.8456          |
| 0.6025        | 6.0   | 180  | 0.6009   | 0.8720          |
| 0.4953        | 7.0   | 210  | 0.5039   | 0.8684          |
| 0.4252        | 8.0   | 240  | 0.4158   | 0.8904          |
| 0.3677        | 9.0   | 270  | 0.3705   | 0.9038          |
| 0.3305        | 10.0  | 300  | 0.3300   | 0.9049          |
| 0.3113        | 11.0  | 330  | 0.3053   | 0.9097          |
| 0.2835        | 12.0  | 360  | 0.2885   | 0.9116          |
| 0.2614        | 13.0  | 390  | 0.2606   | 0.9297          |
| 0.2735        | 14.0  | 420  | 0.2767   | 0.9187          |
| 0.2573        | 15.0  | 450  | 0.2757   | 0.9171          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.0
- Tokenizers 0.13.2