End of training

README.md

@@ -0,0 +1,97 @@
+---
+license: apache-2.0
+base_model: microsoft/swinv2-large-patch4-window12-192-22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swinv2-large-patch4-window12-192-22k-huggingface
+  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: 0.9230769230769231
+---
+
+<!-- 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. -->
+
+# swinv2-large-patch4-window12-192-22k-huggingface
+
+This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-large-patch4-window12-192-22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6329
+- Accuracy: 0.9231
+
+## 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: 0.0001
+- train_batch_size: 18
+- eval_batch_size: 18
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 36
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.781         | 0.97  | 16   | 0.7972          | 0.7385   |
+| 0.5567        | 2.0   | 33   | 0.4750          | 0.8308   |
+| 0.3648        | 2.97  | 49   | 0.5832          | 0.8308   |
+| 0.4016        | 4.0   | 66   | 0.5669          | 0.8      |
+| 0.2448        | 4.97  | 82   | 0.5883          | 0.8462   |
+| 0.3382        | 6.0   | 99   | 0.8846          | 0.8      |
+| 0.3042        | 6.97  | 115  | 0.5364          | 0.8769   |
+| 0.2744        | 8.0   | 132  | 0.5159          | 0.8769   |
+| 0.1859        | 8.97  | 148  | 0.5541          | 0.8462   |
+| 0.1787        | 10.0  | 165  | 0.4850          | 0.8923   |
+| 0.181         | 10.97 | 181  | 0.4529          | 0.9077   |
+| 0.113         | 12.0  | 198  | 0.7836          | 0.8154   |
+| 0.0806        | 12.97 | 214  | 0.7141          | 0.8769   |
+| 0.0929        | 14.0  | 231  | 0.5765          | 0.9231   |
+| 0.1208        | 14.97 | 247  | 0.5762          | 0.9231   |
+| 0.0764        | 16.0  | 264  | 0.6146          | 0.9231   |
+| 0.099         | 16.97 | 280  | 0.5736          | 0.9231   |
+| 0.0972        | 18.0  | 297  | 0.6051          | 0.9231   |
+| 0.0534        | 18.97 | 313  | 0.6302          | 0.9231   |
+| 0.0754        | 19.39 | 320  | 0.6329          | 0.9231   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.1+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

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