update model card README.md

README.md

@@ -0,0 +1,77 @@
+---
+license: other
+base_model: google/mobilenet_v2_0.75_160
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: camera-type
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9866666666666667
+---
+
+<!-- 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. -->
+
+# camera-type
+
+This model is a fine-tuned version of [google/mobilenet_v2_0.75_160](https://huggingface.co/google/mobilenet_v2_0.75_160) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0299
+- Accuracy: 0.9867
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1286        | 1.33  | 200  | 0.0727          | 0.98     |
+| 0.036         | 2.67  | 400  | 0.2050          | 0.9333   |
+| 0.0341        | 4.0   | 600  | 0.0299          | 0.9867   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3