Model save

README.md

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+---
+license: other
+base_model: google/mobilenet_v2_1.4_224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: MobileNet-V2-Retinopathy
+  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: 0.9306930693069307
+---
+
+<!-- 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-Retinopathy
+
+This model is a fine-tuned version of [google/mobilenet_v2_1.4_224](https://huggingface.co/google/mobilenet_v2_1.4_224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2044
+- Accuracy: 0.9307
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4403        | 1.0   | 113  | 0.5330          | 0.7079   |
+| 0.5538        | 2.0   | 227  | 0.4312          | 0.7723   |
+| 0.542         | 3.0   | 340  | 0.5137          | 0.7426   |
+| 0.4776        | 4.0   | 454  | 0.4656          | 0.7723   |
+| 0.4244        | 5.0   | 567  | 1.0400          | 0.5990   |
+| 0.4694        | 6.0   | 681  | 0.5936          | 0.7228   |
+| 0.4494        | 7.0   | 794  | 0.4667          | 0.7822   |
+| 0.4647        | 8.0   | 908  | 0.2629          | 0.8960   |
+| 0.3646        | 9.0   | 1021 | 0.2287          | 0.8861   |
+| 0.4827        | 10.0  | 1135 | 1.7967          | 0.5149   |
+| 0.3679        | 11.0  | 1248 | 0.4184          | 0.8267   |
+| 0.3454        | 12.0  | 1362 | 0.1885          | 0.9406   |
+| 0.3562        | 13.0  | 1475 | 0.2798          | 0.9059   |
+| 0.3397        | 14.0  | 1589 | 1.6444          | 0.5891   |
+| 0.4047        | 14.93 | 1695 | 0.2044          | 0.9307   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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