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# model

This model is a fine-tuned version of [resnet18](https://huggingface.co/resnet18) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0219
- Acc1: 56.3910
- Acc5: 100.0

## 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: 20

### Training results



### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3

{"tags": ["image-classification", "timm", "generated_from_trainer"], "datasets": ["beans"], "library_tag": "timm"}
timm pytorch tensorboard image-classification generated_from_trainer dataset:beans region:us
TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 




# model

This model is a fine-tuned version of resnet18 on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0219
- Acc1: 56.3910
- Acc5: 100.0

## 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: 20

### Training results



### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3

# model

This model is a fine-tuned version of resnet18 on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0219
- Acc1: 56.3910
- Acc5: 100.0 ## 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: 20 ### Training results ### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3
TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 
 # model

This model is a fine-tuned version of resnet18 on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0219
- Acc1: 56.3910
- Acc5: 100.0 ## 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: 20 ### Training results ### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3
passage: TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 
# model

This model is a fine-tuned version of resnet18 on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0219
- Acc1: 56.3910
- Acc5: 100.0## 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: 20### Training results### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3