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# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_05

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1136
- Accuracy: 0.9584
- F1 Score: 0.9562
- Precision: 0.9576

## 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: 100
- eval_batch_size: 100
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 400
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
| 1.2801        | 0.98  | 13   | 0.6953          | 0.7335   | 0.6819   | 0.7815    |
| 0.5928        | 1.96  | 26   | 0.3691          | 0.8440   | 0.8218   | 0.8629    |
| 0.3122        | 2.94  | 39   | 0.1664          | 0.9402   | 0.9377   | 0.9373    |
| 0.1513        | 4.0   | 53   | 0.1292          | 0.9493   | 0.9468   | 0.9467    |
| 0.1227        | 4.98  | 66   | 0.1030          | 0.9601   | 0.9577   | 0.9585    |
| 0.1201        | 5.96  | 79   | 0.1312          | 0.9522   | 0.9496   | 0.9508    |
| 0.0806        | 6.94  | 92   | 0.1306          | 0.9522   | 0.9494   | 0.9520    |
| 0.0645        | 8.0   | 106  | 0.1474          | 0.9482   | 0.9457   | 0.9490    |
| 0.0668        | 8.98  | 119  | 0.0947          | 0.9613   | 0.9589   | 0.9600    |
| 0.0577        | 9.81  | 130  | 0.1136          | 0.9584   | 0.9562   | 0.9576    |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "precision"], "model-index": [{"name": "swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_05", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9584282460136674, "name": "Accuracy"}, {"type": "precision", "value": 0.9575941658443274, "name": "Precision"}]}]}]}
transformers pytorch tensorboard swin image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final\_05
==================================================================


This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1136
* Accuracy: 0.9584
* F1 Score: 0.9562
* Precision: 0.9576


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: 100
* eval\_batch\_size: 100
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 400
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 100
* eval\_batch\_size: 100
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 400
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 100
* eval\_batch\_size: 100
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 400
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3