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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
model-index:
- name: ryan_model314
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. -->
# ryan_model314
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: 0.2532
- Na Accuracy: 0.947
- Ordinal Accuracy: 0.5952
## 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: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|
| 0.3042 | 0.16 | 100 | 0.3673 | 0.928 | 0.4671 |
| 0.2904 | 0.32 | 200 | 0.2977 | 0.933 | 0.5790 |
| 0.2648 | 0.48 | 300 | 0.2831 | 0.944 | 0.5940 |
| 0.3036 | 0.64 | 400 | 0.2776 | 0.949 | 0.5871 |
| 0.2656 | 0.8 | 500 | 0.2846 | 0.931 | 0.6101 |
| 0.2954 | 0.96 | 600 | 0.2532 | 0.947 | 0.5952 |
| 0.1991 | 1.12 | 700 | 0.2603 | 0.942 | 0.6078 |
| 0.1678 | 1.28 | 800 | 0.2905 | 0.942 | 0.6332 |
| 0.2514 | 1.44 | 900 | 0.2566 | 0.94 | 0.6090 |
| 0.2328 | 1.6 | 1000 | 0.2884 | 0.94 | 0.5617 |
| 0.1826 | 1.76 | 1100 | 0.2870 | 0.943 | 0.6044 |
| 0.2013 | 1.92 | 1200 | 0.2937 | 0.941 | 0.5905 |
| 0.0663 | 2.08 | 1300 | 0.2954 | 0.938 | 0.6251 |
| 0.1503 | 2.24 | 1400 | 0.3188 | 0.937 | 0.5986 |
| 0.0611 | 2.4 | 1500 | 0.3393 | 0.945 | 0.5998 |
| 0.0743 | 2.56 | 1600 | 0.3182 | 0.942 | 0.6482 |
| 0.0908 | 2.72 | 1700 | 0.3332 | 0.942 | 0.6482 |
| 0.1108 | 2.88 | 1800 | 0.3256 | 0.943 | 0.6459 |
| 0.0786 | 3.04 | 1900 | 0.3222 | 0.944 | 0.6540 |
| 0.043 | 3.2 | 2000 | 0.3501 | 0.941 | 0.6482 |
| 0.0472 | 3.36 | 2100 | 0.3455 | 0.943 | 0.6609 |
| 0.032 | 3.52 | 2200 | 0.3562 | 0.94 | 0.6517 |
| 0.0434 | 3.68 | 2300 | 0.3499 | 0.94 | 0.6597 |
| 0.0341 | 3.84 | 2400 | 0.3611 | 0.94 | 0.6482 |
| 0.0305 | 4.0 | 2500 | 0.3635 | 0.939 | 0.6609 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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