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mangoes

Image Classification
Transformers
Safetensors
vit
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  ---
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- base_model: google/vit-base-patch16-224-in21k
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  library_name: transformers
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- license: creativeml-openrail-m
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- inference: true
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  tags:
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- - image-classification
 
 
 
 
 
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  ---
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- <!-- This model card has been generated automatically according to the information the training script had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # Image Classification
 
 
 
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- This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the Docty/Mangovariety dataset.
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- You can find some example images in the following.
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- ![img_0](./image_0.png)
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- ![img_1](./image_1.png)
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- ![img_2](./image_2.png)
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- ![img_3](./image_3.png)
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- ## Intended uses & limitations
 
 
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- #### How to use
 
 
 
 
 
 
 
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- ```python
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- # TODO: add an example code snippet for running this diffusion pipeline
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- ```
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- #### Limitations and bias
 
 
 
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- [TODO: provide examples of latent issues and potential remediations]
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- ## Training details
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- [TODO: describe the data used to train the model]
 
 
 
 
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  ---
 
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  library_name: transformers
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: mangoes
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # mangoes
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7385
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+ - Accuracy: 0.9792
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
 
 
 
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 1337
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 2.0
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+ ### Training results
 
 
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.0281 | 1.0 | 170 | 1.0490 | 0.9583 |
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+ | 0.7454 | 2.0 | 340 | 0.7385 | 0.9792 |
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+ ### Framework versions
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+ - Transformers 4.56.1
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.0