update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: segformer-class-classWeights-augmentation
+  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: 0.9545454545454546
+---
+
+<!-- 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. -->
+
+# segformer-class-classWeights-augmentation
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0927
+- Accuracy: 0.9545
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 40
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.96  | 6    | 0.9944          | 0.4773   |
+| 1.0159        | 1.92  | 12   | 0.6948          | 0.75     |
+| 1.0159        | 2.88  | 18   | 0.3417          | 0.9318   |
+| 0.5444        | 4.0   | 25   | 0.2642          | 0.9091   |
+| 0.2331        | 4.96  | 31   | 0.0986          | 0.9545   |
+| 0.2331        | 5.92  | 37   | 0.1735          | 0.9545   |
+| 0.2596        | 6.88  | 43   | 0.1091          | 0.9545   |
+| 0.1737        | 8.0   | 50   | 0.0685          | 0.9545   |
+| 0.1737        | 8.96  | 56   | 0.0995          | 0.9545   |
+| 0.1716        | 9.6   | 60   | 0.0927          | 0.9545   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3