pytorch tensorboard vit image-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modelversion01
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# modelversion01

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 sudo-s/herbier_mesuem1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3888
- Accuracy: 0.7224

## 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1304        | 0.16  | 100  | 3.1546          | 0.3254   |
| 2.6514        | 0.31  | 200  | 2.5058          | 0.4854   |
| 2.0636        | 0.47  | 300  | 2.0647          | 0.5771   |
| 1.7812        | 0.63  | 400  | 1.7536          | 0.6423   |
| 1.5857        | 0.78  | 500  | 1.5272          | 0.6974   |
| 1.3055        | 0.94  | 600  | 1.3888          | 0.7224   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
