---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: regnet-y-064-Brain_Tumors_Image_Classification
  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: 0.8045685279187818
---

<!-- 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. -->

# regnet-y-064-Brain_Tumors_Image_Classification

This model is a fine-tuned version of [facebook/regnet-y-064](https://huggingface.co/facebook/regnet-y-064) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1561
- Accuracy: 0.8046
- Weighted f1: 0.7776
- Micro f1: 0.8046
- Macro f1: 0.7839
- Weighted recall: 0.8046
- Micro recall: 0.8046
- Macro recall: 0.7978
- Weighted precision: 0.8574
- Micro precision: 0.8046
- Macro precision: 0.8736

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 1.288         | 1.0   | 180  | 1.3796          | 0.6548   | 0.5991      | 0.6548   | 0.5868   | 0.6548          | 0.6548       | 0.6176       | 0.8046             | 0.6548          | 0.8285          |
| 1.288         | 2.0   | 360  | 1.0964          | 0.7944   | 0.7687      | 0.7944   | 0.7755   | 0.7944          | 0.7944       | 0.7872       | 0.8555             | 0.7944          | 0.8727          |
| 0.1498        | 3.0   | 540  | 1.1561          | 0.8046   | 0.7776      | 0.8046   | 0.7839   | 0.8046          | 0.8046       | 0.7978       | 0.8574             | 0.8046          | 0.8736          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3