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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: other
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+ base_model: google/mobilenet_v2_1.0_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: mobilenet_v2_1.0_224-finetuned-plantdisease
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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: 0.9447674418604651
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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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+ # mobilenet_v2_1.0_224-finetuned-plantdisease
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+
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+ This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1663
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+ - Accuracy: 0.9448
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 20
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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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+ | 1.7982 | 0.9983 | 145 | 1.9825 | 0.4036 |
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+ | 0.6137 | 1.9966 | 290 | 1.1130 | 0.6415 |
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+ | 0.4176 | 2.9948 | 435 | 0.4887 | 0.8469 |
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+ | 0.3107 | 4.0 | 581 | 0.3414 | 0.8944 |
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+ | 0.2255 | 4.9983 | 726 | 0.2732 | 0.9123 |
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+ | 0.1833 | 5.9966 | 871 | 0.7462 | 0.7582 |
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+ | 0.2062 | 6.9948 | 1016 | 0.3771 | 0.8803 |
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+ | 0.1657 | 8.0 | 1162 | 0.4718 | 0.8542 |
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+ | 0.1427 | 8.9983 | 1307 | 0.4902 | 0.8474 |
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+ | 0.1598 | 9.9966 | 1452 | 0.2229 | 0.9273 |
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+ | 0.1504 | 10.9948 | 1597 | 0.3021 | 0.8973 |
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+ | 0.1456 | 12.0 | 1743 | 0.2422 | 0.9225 |
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+ | 0.119 | 12.9983 | 1888 | 0.2836 | 0.9021 |
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+ | 0.114 | 13.9966 | 2033 | 0.2038 | 0.9293 |
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+ | 0.1378 | 14.9948 | 2178 | 0.2173 | 0.9239 |
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+ | 0.1249 | 16.0 | 2324 | 0.2467 | 0.9186 |
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+ | 0.1504 | 16.9983 | 2469 | 0.2322 | 0.9254 |
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+ | 0.0972 | 17.9966 | 2614 | 0.0841 | 0.9782 |
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+ | 0.1293 | 18.9948 | 2759 | 0.1512 | 0.9467 |
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+ | 0.1072 | 19.9656 | 2900 | 0.1663 | 0.9448 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.19.1
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