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# vit-base-beans-2

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: 1.1144
- Accuracy: 0.375

## 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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.1243          | 0.4375   |
| No log        | 2.0   | 4    | 1.1204          | 0.375    |
| No log        | 3.0   | 6    | 1.1172          | 0.375    |
| No log        | 4.0   | 8    | 1.1152          | 0.375    |
| 0.9751        | 5.0   | 10   | 1.1144          | 0.375    |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1
- Datasets 2.15.1.dev0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["image-classification", "vision", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "vit-base-beans-2", "results": []}]}
transformers tensorboard safetensors vit image-classification vision generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us