Model save

README.md

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+---
+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-augmented
+  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: 0.8439716312056738
+---
+
+<!-- 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-augmented
+
+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: 0.4230
+- Accuracy: 0.8440
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 5    | 0.8342          | 0.7447   |
+| 1.3135        | 2.0   | 10   | 0.6567          | 0.7872   |
+| 1.3135        | 3.0   | 15   | 0.4849          | 0.8227   |
+| 0.4762        | 4.0   | 20   | 0.4877          | 0.8440   |
+| 0.4762        | 5.0   | 25   | 0.4230          | 0.8440   |
+
+
+### 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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