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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-tiny-patch4-window8-256 |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: swinv2-tiny-patch4-window8-256-finetuned-galaxy10-decals |
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results: [] |
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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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# swinv2-tiny-patch4-window8-256-finetuned-galaxy10-decals |
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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 matthieulel/galaxy10_decals dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4357 |
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- Accuracy: 0.8585 |
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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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| 1.318 | 0.9940 | 124 | 1.0409 | 0.6359 | |
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| 0.9268 | 1.9960 | 249 | 0.7164 | 0.7497 | |
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| 0.8221 | 2.9980 | 374 | 0.6210 | 0.7875 | |
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| 0.7276 | 4.0 | 499 | 0.5564 | 0.8162 | |
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| 0.6425 | 4.9940 | 623 | 0.5226 | 0.8162 | |
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| 0.6518 | 5.9960 | 748 | 0.5377 | 0.8185 | |
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| 0.6096 | 6.9980 | 873 | 0.5341 | 0.8219 | |
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| 0.6282 | 8.0 | 998 | 0.4718 | 0.8399 | |
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| 0.5394 | 8.9940 | 1122 | 0.5113 | 0.8281 | |
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| 0.5718 | 9.9960 | 1247 | 0.5019 | 0.8292 | |
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| 0.5507 | 10.9980 | 1372 | 0.4545 | 0.8461 | |
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| 0.4921 | 12.0 | 1497 | 0.4613 | 0.8416 | |
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| 0.5571 | 12.9940 | 1621 | 0.4587 | 0.8416 | |
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| 0.512 | 13.9960 | 1746 | 0.4673 | 0.8512 | |
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| 0.4855 | 14.9980 | 1871 | 0.4641 | 0.8489 | |
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| 0.4895 | 16.0 | 1996 | 0.4556 | 0.8450 | |
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| 0.4809 | 16.9940 | 2120 | 0.4317 | 0.8523 | |
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| 0.4785 | 17.9960 | 2245 | 0.4338 | 0.8534 | |
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| 0.444 | 18.9980 | 2370 | 0.4357 | 0.8579 | |
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| 0.4255 | 19.8798 | 2480 | 0.4357 | 0.8585 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 1.12.1+cu116 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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