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: swin-tiny-patch4-window7-224-mulder-v-scully-colab2
+  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: 1.0
+---
+
+<!-- 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-tiny-patch4-window7-224-mulder-v-scully-colab2
+
+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: 0.3970
+- Accuracy: 1.0
+
+## 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 1    | 0.6899          | 0.5      |
+| No log        | 2.0   | 2    | 0.6701          | 0.25     |
+| No log        | 3.0   | 3    | 0.6309          | 0.5      |
+| No log        | 4.0   | 4    | 0.6049          | 0.5      |
+| No log        | 5.0   | 5    | 0.5828          | 0.5      |
+| No log        | 6.0   | 6    | 0.5650          | 0.75     |
+| No log        | 7.0   | 7    | 0.5486          | 0.75     |
+| No log        | 8.0   | 8    | 0.5344          | 1.0      |
+| No log        | 9.0   | 9    | 0.5240          | 1.0      |
+| 0.2978        | 10.0  | 10   | 0.5149          | 1.0      |
+| 0.2978        | 11.0  | 11   | 0.5066          | 1.0      |
+| 0.2978        | 12.0  | 12   | 0.4980          | 1.0      |
+| 0.2978        | 13.0  | 13   | 0.4880          | 1.0      |
+| 0.2978        | 14.0  | 14   | 0.4699          | 1.0      |
+| 0.2978        | 15.0  | 15   | 0.4507          | 1.0      |
+| 0.2978        | 16.0  | 16   | 0.4310          | 1.0      |
+| 0.2978        | 17.0  | 17   | 0.4155          | 1.0      |
+| 0.2978        | 18.0  | 18   | 0.4054          | 1.0      |
+| 0.2978        | 19.0  | 19   | 0.3994          | 1.0      |
+| 0.1751        | 20.0  | 20   | 0.3970          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3