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Plant-Disease-Detection-Project

Image Classification
Transformers
Safetensors
mobilenet_v2
vision
Inference Endpoints
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+ ---
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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: mobilenet_v2_1.0_224-plant-disease-new
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+ results: []
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+ datasets:
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+ - A2H0H0R1/plant-disease-new
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+ pipeline_tag: image-classification
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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-plant-disease-new
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1287
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+ - Accuracy: 0.9600
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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: 100
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+ - eval_batch_size: 100
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 400
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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: 6
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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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+ | 0.5043 | 1.0 | 366 | 0.4476 | 0.8886 |
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+ | 0.2492 | 2.0 | 733 | 0.2550 | 0.9281 |
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+ | 0.2069 | 3.0 | 1100 | 0.2332 | 0.9247 |
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+ | 0.1716 | 4.0 | 1467 | 0.3329 | 0.8960 |
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+ | 0.1602 | 5.0 | 1833 | 0.1999 | 0.9388 |
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+ | 0.1633 | 5.99 | 2196 | 0.1287 | 0.9600 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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+ "train_steps_per_second": 0.282
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+ }
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+ "_name_or_path": "google/mobilenet_v2_1.0_224",
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+ "MobileNetV2ForImageClassification"
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+ ],
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+ "first_layer_is_expansion": true,
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+ "hidden_act": "relu6",
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+ "id2label": {
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+ "0": "Apple Apple scab",
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+ "1": "Apple Black rot",
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+ "2": "Apple Cedar apple rust",
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+ "3": "Apple healthy",
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+ "4": "Blueberry healthy",
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+ "5": "Cherry (including sour) Powdery mildew",
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+ "6": "Cherry (including sour) healthy",
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+ "7": "Corn (maize) Cercospora leaf spot Gray leaf spot",
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+ "8": "Corn (maize) Common rust ",
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+ "9": "Corn (maize) Northern Leaf Blight",
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+ "10": "Corn (maize) healthy",
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+ "12": "Grape Esca (Black Measles)",
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+ "13": "Grape Leaf blight (Isariopsis Leaf Spot)",
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+ "14": "Grape healthy",
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+ "15": "Orange Haunglongbing (Citrus greening)",
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+ "16": "Peach Bacterial spot",
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+ "17": "Peach healthy",
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+ "18": "Pepper, bell Bacterial spot",
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+ "19": "Pepper, bell healthy",
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+ "20": "Potato Early blight",
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+ "21": "Potato Late blight",
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+ "22": "Potato healthy",
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+ "23": "Raspberry healthy",
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+ "24": "Soybean healthy",
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+ "26": "Strawberry Leaf scorch",
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+ "27": "Strawberry healthy",
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+ "28": "Tomato Bacterial spot",
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+ "30": "Tomato Late blight",
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+ "31": "Tomato Leaf Mold",
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+ "32": "Tomato Septoria leaf spot",
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+ "33": "Tomato Spider mites Two-spotted spider mite",
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+ "34": "Tomato Target Spot",
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+ "35": "Tomato Tomato Yellow Leaf Curl Virus",
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+ "36": "Tomato Tomato mosaic virus",
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+ "37": "Tomato healthy"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "Tomato Tomato Yellow Leaf Curl Virus": 35,
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+ "Tomato Tomato mosaic virus": 36,
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+ "Tomato healthy": 37
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+ },
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+ "layer_norm_eps": 0.001,
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+ "min_depth": 8,
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+ "model_type": "mobilenet_v2",
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+ "num_channels": 3,
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+ "output_stride": 32,
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+ "problem_type": "single_label_classification",
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+ "semantic_loss_ignore_index": 255,
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+ "total_flos": 2.353803972968448e+18,
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+ "trial_name": null,
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+ "trial_params": null
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+ }
training_args.bin ADDED
Binary file (4.6 kB). View file