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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_3
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_3
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: 0.2750
- Na Accuracy: 0.931
- Ordinal Accuracy: 0.6271
- Ordinal Mae: 0.5319
## 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: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy | Ordinal Mae |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
| 0.4423 | 0.08 | 50 | 0.3386 | 0.904 | 0.4629 | 0.6578 |
| 0.3088 | 0.16 | 100 | 0.3269 | 0.928 | 0.5371 | 0.5969 |
| 0.316 | 0.24 | 150 | 0.3396 | 0.902 | 0.5143 | 0.6323 |
| 0.2821 | 0.32 | 200 | 0.3234 | 0.927 | 0.5131 | 0.6293 |
| 0.2731 | 0.4 | 250 | 0.3314 | 0.925 | 0.5086 | 0.5856 |
| 0.2975 | 0.48 | 300 | 0.3037 | 0.927 | 0.5964 | 0.5690 |
| 0.2609 | 0.56 | 350 | 0.3209 | 0.928 | 0.5450 | 0.5765 |
| 0.287 | 0.64 | 400 | 0.2908 | 0.931 | 0.5827 | 0.5458 |
| 0.2905 | 0.72 | 450 | 0.3007 | 0.919 | 0.5986 | 0.5484 |
| 0.2574 | 0.8 | 500 | 0.2834 | 0.929 | 0.6032 | 0.5363 |
| 0.2855 | 0.88 | 550 | 0.2750 | 0.931 | 0.6271 | 0.5319 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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