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# vit_beans

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1176
- Accuracy: 0.9699

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 2.0.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["beans"], "metrics": ["accuracy"], "model-index": [{"name": "vit_beans", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "beans", "type": "beans", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9699248120300752, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:beans license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-beans #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 




# vit_beans

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1176
- Accuracy: 0.9699

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 2.0.0
- Tokenizers 0.10.3

# vit_beans

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1176
- Accuracy: 0.9699 ## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 2.0.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-beans #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # vit_beans

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1176
- Accuracy: 0.9699 ## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 2.0.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-beans #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
# vit_beans

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1176
- Accuracy: 0.9699## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1### Training results### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 2.0.0
- Tokenizers 0.10.3