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# vit-base-patch16-224-cifar10

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 cifar10 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["cifar10"], "model-index": [{"name": "vit-base-patch16-224-cifar10", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "cifar10", "type": "cifar10", "config": "plain_text", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.1004, "name": "Accuracy", "verified": true}, {"type": "precision", "value": 0.07725693204097324, "name": "Precision Macro", "verified": true}, {"type": "precision", "value": 0.1004, "name": "Precision Micro", "verified": true}, {"type": "precision", "value": 0.07725693204097323, "name": "Precision Weighted", "verified": true}, {"type": "recall", "value": 0.1004, "name": "Recall Macro", "verified": true}, {"type": "recall", "value": 0.1004, "name": "Recall Micro", "verified": true}, {"type": "recall", "value": 0.1004, "name": "Recall Weighted", "verified": true}, {"type": "f1", "value": 0.07942008420616108, "name": "F1 Macro", "verified": true}, {"type": "f1", "value": 0.1004, "name": "F1 Micro", "verified": true}, {"type": "f1", "value": 0.07942008420616108, "name": "F1 Weighted", "verified": true}, {"type": "loss", "value": 2.3154706954956055, "name": "loss", "verified": true}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:cifar10 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-cifar10 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 




# vit-base-patch16-224-cifar10

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar10 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1

# vit-base-patch16-224-cifar10

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar10 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-cifar10 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # vit-base-patch16-224-cifar10

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar10 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-cifar10 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
# vit-base-patch16-224-cifar10

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar10 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.1
- Datasets 2.1.0
- Tokenizers 0.12.1