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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-22k-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: Expert2-leaf-disease-convnextv2-base-22k-224-1_2_3
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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: 0.9498025944726453
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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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+ # Expert2-leaf-disease-convnextv2-base-22k-224-1_2_3
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1599
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+ - Accuracy: 0.9498
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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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+ | 1.0623 | 0.96 | 13 | 0.6227 | 0.7456 |
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+ | 0.5754 | 2.0 | 27 | 0.2772 | 0.8996 |
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+ | 0.233 | 2.96 | 40 | 0.2167 | 0.9255 |
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+ | 0.1972 | 4.0 | 54 | 0.1777 | 0.9425 |
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+ | 0.1763 | 4.96 | 67 | 0.1742 | 0.9425 |
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+ | 0.1631 | 6.0 | 81 | 0.1650 | 0.9459 |
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+ | 0.1532 | 6.96 | 94 | 0.1708 | 0.9391 |
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+ | 0.1384 | 8.0 | 108 | 0.1627 | 0.9442 |
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+ | 0.1415 | 8.96 | 121 | 0.1662 | 0.9447 |
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+ | 0.133 | 10.0 | 135 | 0.1620 | 0.9470 |
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+ | 0.1362 | 10.96 | 148 | 0.1715 | 0.9442 |
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+ | 0.1248 | 12.0 | 162 | 0.1628 | 0.9447 |
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+ | 0.1217 | 12.96 | 175 | 0.1607 | 0.9475 |
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+ | 0.1264 | 14.0 | 189 | 0.1587 | 0.9475 |
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+ | 0.1178 | 14.96 | 202 | 0.1595 | 0.9498 |
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+ | 0.1178 | 15.41 | 208 | 0.1599 | 0.9498 |
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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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