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--- |
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license: apache-2.0 |
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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-mulder-v-scully-colab2 |
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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: 1.0 |
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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-mulder-v-scully-colab2 |
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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: 0.5344 |
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- Accuracy: 1.0 |
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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: 20 |
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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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| No log | 1.0 | 1 | 0.6899 | 0.5 | |
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| No log | 2.0 | 2 | 0.6701 | 0.25 | |
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| No log | 3.0 | 3 | 0.6309 | 0.5 | |
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| No log | 4.0 | 4 | 0.6049 | 0.5 | |
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| No log | 5.0 | 5 | 0.5828 | 0.5 | |
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| No log | 6.0 | 6 | 0.5650 | 0.75 | |
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| No log | 7.0 | 7 | 0.5486 | 0.75 | |
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| No log | 8.0 | 8 | 0.5344 | 1.0 | |
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| No log | 9.0 | 9 | 0.5240 | 1.0 | |
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| 0.2978 | 10.0 | 10 | 0.5149 | 1.0 | |
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| 0.2978 | 11.0 | 11 | 0.5066 | 1.0 | |
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| 0.2978 | 12.0 | 12 | 0.4980 | 1.0 | |
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| 0.2978 | 13.0 | 13 | 0.4880 | 1.0 | |
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| 0.2978 | 14.0 | 14 | 0.4699 | 1.0 | |
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| 0.2978 | 15.0 | 15 | 0.4507 | 1.0 | |
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| 0.2978 | 16.0 | 16 | 0.4310 | 1.0 | |
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| 0.2978 | 17.0 | 17 | 0.4155 | 1.0 | |
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| 0.2978 | 18.0 | 18 | 0.4054 | 1.0 | |
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| 0.2978 | 19.0 | 19 | 0.3994 | 1.0 | |
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| 0.1751 | 20.0 | 20 | 0.3970 | 1.0 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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