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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/convnextv2-base-1k-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: BaseModel-leaf-disease-convnextv2-base-1k-224-0_1_2_3_4
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8738317757009346
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+ ---
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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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+
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+ # BaseModel-leaf-disease-convnextv2-base-1k-224-0_1_2_3_4
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3737
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+ - Accuracy: 0.8738
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 300
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+ - eval_batch_size: 300
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 1200
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 16
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.9249 | 0.98 | 16 | 0.6211 | 0.7752 |
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+ | 0.5028 | 1.97 | 32 | 0.4815 | 0.8411 |
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+ | 0.4421 | 2.95 | 48 | 0.4503 | 0.8533 |
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+ | 0.4009 | 4.0 | 65 | 0.4187 | 0.8607 |
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+ | 0.3821 | 4.98 | 81 | 0.4080 | 0.8626 |
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+ | 0.3672 | 5.97 | 97 | 0.3952 | 0.8626 |
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+ | 0.3544 | 6.95 | 113 | 0.3927 | 0.8701 |
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+ | 0.3287 | 8.0 | 130 | 0.3848 | 0.8734 |
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+ | 0.327 | 8.98 | 146 | 0.3877 | 0.8696 |
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+ | 0.3239 | 9.97 | 162 | 0.3783 | 0.8701 |
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+ | 0.3113 | 10.95 | 178 | 0.3746 | 0.8724 |
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+ | 0.3146 | 12.0 | 195 | 0.3736 | 0.8734 |
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+ | 0.3031 | 12.98 | 211 | 0.3747 | 0.8692 |
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+ | 0.3075 | 13.97 | 227 | 0.3752 | 0.8738 |
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+ | 0.3071 | 14.95 | 243 | 0.3759 | 0.8762 |
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+ | 0.3028 | 15.75 | 256 | 0.3737 | 0.8738 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.1
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.1
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