Model save
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README.md
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---
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license: apache-2.0
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base_model: microsoft/swin-tiny-patch4-window7-224
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: swin-tiny-patch4-window7-224-hotel_images_classifier_v5_10epocs
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9558704453441296
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# swin-tiny-patch4-window7-224-hotel_images_classifier_v5_10epocs
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1293
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- Accuracy: 0.9559
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.3795 | 1.0 | 694 | 0.1922 | 0.9326 |
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| 0.261 | 2.0 | 1389 | 0.1850 | 0.9335 |
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| 0.2187 | 3.0 | 2084 | 0.1516 | 0.9448 |
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| 0.1491 | 4.0 | 2779 | 0.1360 | 0.9518 |
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| 0.2038 | 5.0 | 3473 | 0.1312 | 0.9514 |
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| 0.1793 | 6.0 | 4168 | 0.1290 | 0.9522 |
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| 0.19 | 7.0 | 4863 | 0.1332 | 0.9533 |
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| 0.1424 | 8.0 | 5558 | 0.1297 | 0.9549 |
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| 0.1555 | 9.0 | 6252 | 0.1303 | 0.9552 |
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| 0.1238 | 9.99 | 6940 | 0.1293 | 0.9559 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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runs/Mar02_08-15-49_260e46876a9c/events.out.tfevents.1709367445.260e46876a9c.192.0
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