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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: fruits_and_vegetables_image_classification
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. -->
# fruits_and_vegetables_image_classification
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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3835
- Accuracy: 0.9159
## 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: 8e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 87 | 1.6751 | 0.8768 |
| No log | 2.0 | 174 | 1.0260 | 0.8957 |
| No log | 3.0 | 261 | 0.6767 | 0.8957 |
| No log | 4.0 | 348 | 0.5445 | 0.8986 |
| No log | 5.0 | 435 | 0.4685 | 0.9072 |
| 0.8955 | 6.0 | 522 | 0.4328 | 0.9072 |
| 0.8955 | 7.0 | 609 | 0.4028 | 0.9 |
| 0.8955 | 8.0 | 696 | 0.3958 | 0.9145 |
| 0.8955 | 9.0 | 783 | 0.3835 | 0.9159 |
| 0.8955 | 10.0 | 870 | 0.3842 | 0.9145 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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