Model save

README.md

@@ -0,0 +1,82 @@
+---
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: hotel_images_classifier_jd_v4_convnext
+  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: 0.936588653351305
+---
+
+<!-- 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. -->
+
+# hotel_images_classifier_jd_v4_convnext
+
+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: 0.1917
+- Accuracy: 0.9366
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3471        | 1.0   | 1147 | 0.2357          | 0.9215   |
+| 0.2737        | 2.0   | 2295 | 0.2133          | 0.9280   |
+| 0.2743        | 3.0   | 3443 | 0.1934          | 0.9355   |
+| 0.276         | 4.0   | 4591 | 0.1982          | 0.9329   |
+| 0.2324        | 5.0   | 5735 | 0.1917          | 0.9366   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.17.1
+- Tokenizers 0.14.1