update model card README.md

README.md

@@ -0,0 +1,77 @@
+---
+license: other
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: mit-b0-finetuned-eurosat
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9494949494949495
+---
+
+<!-- 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. -->
+
+# mit-b0-finetuned-eurosat
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1782
+- Accuracy: 0.9495
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 7    | 0.3828          | 0.8081   |
+| 0.4864        | 2.0   | 14   | 0.2224          | 0.9192   |
+| 0.2035        | 3.0   | 21   | 0.1782          | 0.9495   |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.11.0+cpu
+- Datasets 2.2.0
+- Tokenizers 0.12.1