update model card README.md

README.md

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+---
+license: other
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: mobilenet_v2_1.0_224-plant-disease-identification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7145092460881934
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# mobilenet_v2_1.0_224-plant-disease-identification
+
+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 image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3799
+- Accuracy: 0.7145
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.3889        | 1.0   | 248  | 2.1952          | 0.6310   |
+| 1.8202        | 2.0   | 496  | 1.6363          | 0.7013   |
+| 1.6266        | 3.0   | 744  | 1.6291          | 0.6343   |
+| 1.5566        | 4.0   | 992  | 1.3514          | 0.7129   |
+| 1.5507        | 5.0   | 1240 | 1.3799          | 0.7145   |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.0
+- Datasets 2.1.0
+- Tokenizers 0.13.2