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# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06

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: 0.2384
- Accuracy: 0.9226
- F1 Score: 0.9210
- Precision: 0.9214

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
| 1.3082        | 0.98  | 13   | 0.7669          | 0.7819   | 0.7689   | 0.7723    |
| 0.5415        | 1.96  | 26   | 0.3100          | 0.8867   | 0.8812   | 0.8816    |
| 0.279         | 2.94  | 39   | 0.2901          | 0.8992   | 0.8967   | 0.8961    |
| 0.1563        | 4.0   | 53   | 0.2655          | 0.9089   | 0.9078   | 0.9084    |
| 0.1304        | 4.98  | 66   | 0.2971          | 0.8964   | 0.8935   | 0.8958    |
| 0.1058        | 5.96  | 79   | 0.2358          | 0.9243   | 0.9218   | 0.9224    |
| 0.0971        | 6.94  | 92   | 0.2298          | 0.9260   | 0.9245   | 0.9258    |
| 0.079         | 8.0   | 106  | 0.2468          | 0.9134   | 0.9123   | 0.9125    |
| 0.0638        | 8.98  | 119  | 0.2534          | 0.9112   | 0.9097   | 0.9101    |
| 0.0538        | 9.81  | 130  | 0.2384          | 0.9226   | 0.9210   | 0.9214    |


### 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_06", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9225512528473804, "name": "Accuracy"}, {"type": "precision", "value": 0.9214370287637926, "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\_06
==================================================================


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: 0.2384
* Accuracy: 0.9226
* F1 Score: 0.9210
* Precision: 0.9214


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