End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Balanced-No-Augmentation-swinv2-base
+  results: []
+---
+
+<!-- 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. -->
+
+# Balanced-No-Augmentation-swinv2-base
+
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.6109
+- Accuracy: 0.5692
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 16
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2985        | 0.98  | 11   | 1.4531          | 0.4822   |
+| 0.9081        | 1.97  | 22   | 1.5086          | 0.5731   |
+| 0.4604        | 2.95  | 33   | 1.9810          | 0.5692   |
+| 0.2255        | 3.93  | 44   | 3.0618          | 0.5415   |
+| 0.1339        | 4.92  | 55   | 2.8634          | 0.5613   |
+| 0.0883        | 5.99  | 67   | 3.0244          | 0.5652   |
+| 0.0605        | 6.97  | 78   | 3.5175          | 0.5573   |
+| 0.0506        | 7.96  | 89   | 3.4068          | 0.5850   |
+| 0.0272        | 8.94  | 100  | 3.6996          | 0.5573   |
+| 0.0262        | 9.83  | 110  | 3.6109          | 0.5692   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.15.2

model.safetensors

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