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# test_model_a

This model is a fine-tuned version of [lysandre/tiny-vit-random](https://huggingface.co/lysandre/tiny-vit-random) on the image_folder dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40

### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.1.dev0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["image_folder"], "model_index": [{"name": "test_model_a", "results": [{"task": {"name": "Image Classification", "type": "image-classification"}, "dataset": {"name": "image_folder", "type": "image_folder", "args": "default"}}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:image_folder autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #autotrain_compatible #endpoints_compatible #region-us 




# test_model_a

This model is a fine-tuned version of lysandre/tiny-vit-random on the image_folder dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40

### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.1.dev0
- Tokenizers 0.10.3

# test_model_a

This model is a fine-tuned version of lysandre/tiny-vit-random on the image_folder dataset. ## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40 ### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.1.dev0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #autotrain_compatible #endpoints_compatible #region-us 
 # test_model_a

This model is a fine-tuned version of lysandre/tiny-vit-random on the image_folder dataset. ## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40 ### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.1.dev0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-image_folder #autotrain_compatible #endpoints_compatible #region-us 
# test_model_a

This model is a fine-tuned version of lysandre/tiny-vit-random on the image_folder dataset.## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.1.dev0
- Tokenizers 0.10.3