---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-mango-types
  results: []
---

<!-- 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. -->

# finetuned-mango-types

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5751
- Accuracy: 0.9292

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9926        | 1.0   | 22   | 1.9526          | 0.3833   |
| 1.7976        | 2.0   | 44   | 1.7500          | 0.6083   |
| 1.5678        | 3.0   | 66   | 1.5025          | 0.7583   |
| 1.3907        | 4.0   | 88   | 1.2804          | 0.9      |
| 1.0873        | 5.0   | 110  | 1.1005          | 0.9042   |
| 0.9511        | 6.0   | 132  | 1.0130          | 0.8875   |
| 0.8476        | 7.0   | 154  | 0.9424          | 0.8833   |
| 0.7511        | 8.0   | 176  | 0.8325          | 0.9042   |
| 0.6985        | 9.0   | 198  | 0.7894          | 0.9083   |
| 0.6515        | 10.0  | 220  | 0.8052          | 0.8792   |
| 0.5775        | 11.0  | 242  | 0.7600          | 0.8792   |
| 0.5458        | 12.0  | 264  | 0.6684          | 0.925    |
| 0.5331        | 13.0  | 286  | 0.7148          | 0.8917   |
| 0.4823        | 14.0  | 308  | 0.6849          | 0.9125   |
| 0.4579        | 15.0  | 330  | 0.6414          | 0.9167   |
| 0.4435        | 16.0  | 352  | 0.6557          | 0.8833   |
| 0.4411        | 17.0  | 374  | 0.5968          | 0.9083   |
| 0.453         | 18.0  | 396  | 0.5751          | 0.9292   |
| 0.445         | 19.0  | 418  | 0.6035          | 0.9083   |
| 0.4357        | 20.0  | 440  | 0.6010          | 0.9083   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2