Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window12-192-22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: SwinV2-Base-30VN-Food
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8628968253968254
+---
+
+<!-- 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-Base-30VN-Food
+
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4828
+- Accuracy: 0.8629
+
+## 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: 0.0003
+- train_batch_size: 64
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8268        | 1.0   | 275  | 0.5937          | 0.8270   |
+| 0.5113        | 2.0   | 550  | 0.5267          | 0.8545   |
+| 0.331         | 3.0   | 825  | 0.5459          | 0.8545   |
+| 0.2273        | 4.0   | 1100 | 0.6090          | 0.8441   |
+| 0.1384        | 5.0   | 1375 | 0.6096          | 0.8736   |
+| 0.0918        | 6.0   | 1650 | 0.6669          | 0.8414   |
+| 0.0616        | 7.0   | 1925 | 0.6487          | 0.8891   |
+| 0.0307        | 8.0   | 2200 | 0.6908          | 0.8787   |
+| 0.0173        | 9.0   | 2475 | 0.6673          | 0.8938   |
+| 0.0109        | 10.0  | 2750 | 0.6488          | 0.9014   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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runs/May19_13-03-09_e6724a92e086/events.out.tfevents.1716132096.e6724a92e086.34.1

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