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# test

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: 2.2724
- F1: 0.1240

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 0.001

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.0   | 1    | 2.2724          | 0.1240 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["image_folder"], "metrics": ["f1"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "test", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "image_folder", "type": "image_folder", "args": "default"}, "metrics": [{"type": "f1", "value": 0.12404601272248332, "name": "F1"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:image_folder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #base_model-facebook/deit-tiny-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

test
====


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: 2.2724
* F1: 0.1240


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: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 0.001


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 0.001 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #base_model-facebook/deit-tiny-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 0.001 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #base_model-facebook/deit-tiny-patch16-224 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 0.001### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0
* Datasets 2.0.0
* Tokenizers 0.11.6