update model card README.md

README.md

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+---
+license: other
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: mobilenet_v1_0.75_192-finetuned-eurosat
+  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: 0.3103448275862069
+---
+
+<!-- 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_v1_0.75_192-finetuned-eurosat
+
+This model is a fine-tuned version of [google/mobilenet_v1_0.75_192](https://huggingface.co/google/mobilenet_v1_0.75_192) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3344
+- Accuracy: 0.3103
+
+## 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: 0.0002
+- train_batch_size: 1
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3566        | 1.0   | 65   | 1.3639          | 0.3103   |
+| 0.9354        | 2.0   | 130  | 1.4389          | 0.2759   |
+| 0.8786        | 3.0   | 195  | 1.3344          | 0.3103   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 1.12.1
+- Datasets 2.12.0
+- Tokenizers 0.13.3