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# deit-tiny-patch16-224-finetuned-eurosat

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1779
- Accuracy: 0.9192

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 7    | 0.3528          | 0.8283   |
| 0.5571        | 2.0   | 14   | 0.2141          | 0.8788   |
| 0.197         | 3.0   | 21   | 0.1779          | 0.9192   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.2.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["image_folder"], "metrics": ["accuracy"], "model-index": [{"name": "deit-tiny-patch16-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "image_folder", "type": "image_folder", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9191919191919192, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:image_folder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

deit-tiny-patch16-224-finetuned-eurosat
=======================================


This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the image\_folder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1779
* Accuracy: 0.9192


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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.2.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.2.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.2.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.2.0
* Tokenizers 0.12.1