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README.md
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---
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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
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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: 0.6845918083031485
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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
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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8630
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- Accuracy: 0.6846
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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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| 1.3586 | 1.0 | 252 | 1.2051 | 0.5403 |
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| 1.2281 | 2.0 | 505 | 1.0535 | 0.6108 |
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| 1.148 | 3.0 | 757 | 0.9985 | 0.6194 |
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| 1.087 | 4.0 | 1010 | 0.9658 | 0.6361 |
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| 1.1121 | 5.0 | 1262 | 0.9203 | 0.6539 |
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| 1.0127 | 6.0 | 1515 | 0.9245 | 0.6567 |
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| 0.9858 | 7.0 | 1767 | 0.8846 | 0.6757 |
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| 0.9948 | 8.0 | 2020 | 0.8793 | 0.6748 |
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| 0.9398 | 9.0 | 2272 | 0.8671 | 0.6765 |
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| 0.9904 | 9.98 | 2520 | 0.8630 | 0.6846 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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