
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# plant-seedlings-model-aug-3

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2365
- eval_accuracy: 0.9613
- eval_runtime: 29.5637
- eval_samples_per_second: 61.224
- eval_steps_per_second: 7.678
- epoch: 23.4
- step: 4400

## 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: 24
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "model-index": [{"name": "plant-seedlings-model-aug-3", "results": []}]}
transformers pytorch tensorboard vit image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 




# plant-seedlings-model-aug-3

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2365
- eval_accuracy: 0.9613
- eval_runtime: 29.5637
- eval_samples_per_second: 61.224
- eval_steps_per_second: 7.678
- epoch: 23.4
- step: 4400

## 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: 24
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# plant-seedlings-model-aug-3

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2365
- eval_accuracy: 0.9613
- eval_runtime: 29.5637
- eval_samples_per_second: 61.224
- eval_steps_per_second: 7.678
- epoch: 23.4
- step: 4400 ## 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: 24
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # plant-seedlings-model-aug-3

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2365
- eval_accuracy: 0.9613
- eval_runtime: 29.5637
- eval_samples_per_second: 61.224
- eval_steps_per_second: 7.678
- epoch: 23.4
- step: 4400 ## 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: 24
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# plant-seedlings-model-aug-3

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2365
- eval_accuracy: 0.9613
- eval_runtime: 29.5637
- eval_samples_per_second: 61.224
- eval_steps_per_second: 7.678
- epoch: 23.4
- step: 4400## 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: 24
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3