update model card README.md

README.md

@@ -0,0 +1,77 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- food101
+metrics:
+- accuracy
+model-index:
+- name: swin-finetuned-food101
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: food101
+      type: food101
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9214257425742575
+---
+
+<!-- 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. -->
+
+# swin-finetuned-food101
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the food101 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2779
+- Accuracy: 0.9214
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5646        | 1.0   | 1183 | 0.3937          | 0.8861   |
+| 0.3327        | 2.0   | 2366 | 0.3024          | 0.9124   |
+| 0.1042        | 3.0   | 3549 | 0.2779          | 0.9214   |
+
+
+### Framework versions
+
+- Transformers 4.20.0
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1