---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: resnet-Alzheimer
  results: []
datasets:
  - Falah/Alzheimer_MRI
---

<!-- 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-Alzheimer

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on [Falah/Alzheimer_MRI](https://huggingface.co/datasets/Falah/Alzheimer_MRI) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0932
- Accuracy: 0.9795

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.002
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0127        | 1.0   | 80   | 0.9888          | 0.5088   |
| 0.9345        | 2.0   | 160  | 0.9422          | 0.5303   |
| 0.8889        | 3.0   | 240  | 0.8724          | 0.5781   |
| 0.8843        | 4.0   | 320  | 0.8536          | 0.5889   |
| 0.8397        | 5.0   | 400  | 0.8354          | 0.6152   |
| 0.8624        | 6.0   | 480  | 0.9221          | 0.5381   |
| 0.7543        | 7.0   | 560  | 0.7568          | 0.6475   |
| 0.6993        | 8.0   | 640  | 0.8830          | 0.6133   |
| 0.7045        | 9.0   | 720  | 0.7373          | 0.6582   |
| 0.6557        | 10.0  | 800  | 0.6076          | 0.7451   |
| 0.5876        | 11.0  | 880  | 0.7281          | 0.6992   |
| 0.5732        | 12.0  | 960  | 0.5769          | 0.7510   |
| 0.4864        | 13.0  | 1040 | 0.4457          | 0.8311   |
| 0.5175        | 14.0  | 1120 | 0.5278          | 0.7842   |
| 0.4865        | 15.0  | 1200 | 0.4164          | 0.8379   |
| 0.4049        | 16.0  | 1280 | 0.4204          | 0.8301   |
| 0.4167        | 17.0  | 1360 | 0.4720          | 0.8281   |
| 0.36          | 18.0  | 1440 | 0.4660          | 0.8164   |
| 0.3195        | 19.0  | 1520 | 0.3064          | 0.8770   |
| 0.3652        | 20.0  | 1600 | 0.2571          | 0.9121   |
| 0.2794        | 21.0  | 1680 | 0.2450          | 0.9150   |
| 0.2704        | 22.0  | 1760 | 0.2391          | 0.9033   |
| 0.2612        | 23.0  | 1840 | 0.2352          | 0.9277   |
| 0.2425        | 24.0  | 1920 | 0.4720          | 0.8281   |
| 0.2567        | 25.0  | 2000 | 0.2296          | 0.9131   |
| 0.2302        | 26.0  | 2080 | 0.3067          | 0.8945   |
| 0.2358        | 27.0  | 2160 | 0.1776          | 0.9375   |
| 0.2173        | 28.0  | 2240 | 0.1596          | 0.9492   |
| 0.1798        | 29.0  | 2320 | 0.1548          | 0.9414   |
| 0.197         | 30.0  | 2400 | 0.1740          | 0.9570   |
| 0.1654        | 31.0  | 2480 | 0.1217          | 0.9668   |
| 0.1896        | 32.0  | 2560 | 0.2552          | 0.9258   |
| 0.1705        | 33.0  | 2640 | 0.1031          | 0.9727   |
| 0.1689        | 34.0  | 2720 | 0.1011          | 0.9688   |
| 0.1439        | 35.0  | 2800 | 0.1175          | 0.9648   |
| 0.1606        | 36.0  | 2880 | 0.1805          | 0.9443   |
| 0.1281        | 37.0  | 2960 | 0.1254          | 0.9678   |
| 0.1518        | 38.0  | 3040 | 0.1184          | 0.9648   |
| 0.1531        | 39.0  | 3120 | 0.0992          | 0.9736   |
| 0.132         | 40.0  | 3200 | 0.0920          | 0.9775   |
| 0.134         | 41.0  | 3280 | 0.1391          | 0.9639   |
| 0.1413        | 42.0  | 3360 | 0.1122          | 0.9717   |
| 0.1097        | 43.0  | 3440 | 0.1171          | 0.9678   |
| 0.1167        | 44.0  | 3520 | 0.1054          | 0.9766   |
| 0.1388        | 45.0  | 3600 | 0.0932          | 0.9795   |
| 0.1221        | 46.0  | 3680 | 0.0946          | 0.9766   |
| 0.1099        | 47.0  | 3760 | 0.1116          | 0.9756   |
| 0.1041        | 48.0  | 3840 | 0.1126          | 0.9746   |
| 0.1025        | 49.0  | 3920 | 0.1114          | 0.9756   |
| 0.0887        | 50.0  | 4000 | 0.1056          | 0.9756   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2