Model save

README.md

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+---
+license: other
+base_model: google/mobilenet_v2_1.0_224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: mobilenet_v2_1.0_224-plant-disease2
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9638691322901849
+---
+
+<!-- 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-disease2
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.1510
+- Accuracy: 0.9639
+
+## 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: 5e-05
+- train_batch_size: 100
+- eval_batch_size: 100
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 400
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2171        | 1.0   | 158  | 1.0595          | 0.8188   |
+| 0.4082        | 2.0   | 316  | 0.3154          | 0.9387   |
+| 0.295         | 3.0   | 474  | 0.2191          | 0.9555   |
+| 0.2266        | 4.0   | 633  | 0.1747          | 0.9595   |
+| 0.2168        | 5.0   | 791  | 0.2135          | 0.9499   |
+| 0.2091        | 5.99  | 948  | 0.1510          | 0.9639   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0