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---
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
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