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
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-base-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: 0.0639
- Accuracy: 0.9925

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2804        | 1.0   | 130  | 0.2198          | 0.9624   |
| 0.1304        | 2.0   | 260  | 0.1258          | 0.9699   |
| 0.1388        | 3.0   | 390  | 0.0927          | 0.9774   |
| 0.088         | 4.0   | 520  | 0.0639          | 0.9925   |
| 0.1175        | 5.0   | 650  | 0.0837          | 0.9774   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2
