Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-tiny-patch4-window8-256
+tags:
+- generated_from_trainer
+datasets:
+- food101
+metrics:
+- accuracy
+model-index:
+- name: swinv2-tiny-patch4-window8-256-finetuned-eurosat
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: food101
+      type: food101
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8858613861386139
+---
+
+<!-- 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-tiny-patch4-window8-256-finetuned-eurosat
+
+This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the food101 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3997
+- Accuracy: 0.8859
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8552        | 1.0   | 592  | 1.1245          | 0.6955   |
+| 1.2938        | 2.0   | 1184 | 0.6712          | 0.8131   |
+| 1.2294        | 3.0   | 1776 | 0.5354          | 0.8492   |
+| 1.0199        | 4.0   | 2368 | 0.4958          | 0.8594   |
+| 0.9914        | 5.0   | 2960 | 0.4633          | 0.8678   |
+| 0.8786        | 6.0   | 3552 | 0.4390          | 0.8750   |
+| 0.806         | 7.0   | 4144 | 0.4206          | 0.8791   |
+| 0.7506        | 8.0   | 4736 | 0.4093          | 0.8832   |
+| 0.7433        | 9.0   | 5328 | 0.4053          | 0.8841   |
+| 0.6393        | 10.0  | 5920 | 0.3997          | 0.8859   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3