Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-base-patch4-window12-384
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500
+  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. -->
+
+# 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window12-384](https://huggingface.co/microsoft/swin-base-patch4-window12-384) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3023
+- Accuracy: 0.9339
+- Precision: 0.9335
+- Recall: 0.9314
+- F1: 0.9313
+
+## 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: 0.0005
+- train_batch_size: 25
+- eval_batch_size: 25
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 100
+- 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 | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.786         | 1.0   | 80   | 0.6341          | 0.7918   | 0.8135    | 0.7860 | 0.7830 |
+| 0.6519        | 2.0   | 160  | 0.6522          | 0.7958   | 0.8177    | 0.7913 | 0.7840 |
+| 0.6352        | 3.0   | 240  | 0.5289          | 0.8328   | 0.8473    | 0.8255 | 0.8258 |
+| 0.4922        | 4.0   | 320  | 0.5681          | 0.8448   | 0.8680    | 0.8386 | 0.8396 |
+| 0.3959        | 5.0   | 400  | 0.3896          | 0.8799   | 0.8816    | 0.8772 | 0.8755 |
+| 0.3277        | 6.0   | 480  | 0.3588          | 0.9119   | 0.9073    | 0.9104 | 0.9080 |
+| 0.284         | 7.0   | 560  | 0.3355          | 0.9099   | 0.9126    | 0.9066 | 0.9058 |
+| 0.2075        | 8.0   | 640  | 0.2876          | 0.9289   | 0.9271    | 0.9287 | 0.9269 |
+| 0.1751        | 9.0   | 720  | 0.2871          | 0.9349   | 0.9337    | 0.9320 | 0.9321 |
+| 0.1923        | 10.0  | 800  | 0.3023          | 0.9339   | 0.9335    | 0.9314 | 0.9313 |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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