End of training
Browse files- README.md +30 -20
- all_results.json +10 -10
- eval_results.json +6 -6
- model.safetensors +1 -1
- runs/Dec28_00-52-56_MacBook-Pro-de-Max-2.local/events.out.tfevents.1703721182.MacBook-Pro-de-Max-2.local.31343.9 +3 -0
- runs/Dec28_00-52-56_MacBook-Pro-de-Max-2.local/events.out.tfevents.1703723525.MacBook-Pro-de-Max-2.local.31343.10 +3 -0
- train_results.json +5 -5
- trainer_state.json +303 -129
- training_args.bin +1 -1
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 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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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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## Intended uses & limitations
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8389261744966443
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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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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5312
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- Accuracy: 0.8389
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## Model description
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+
More information needed
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## Intended uses & limitations
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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: 25
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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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| 1.6068 | 0.97 | 14 | 1.5809 | 0.5415 |
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| 1.56 | 2.0 | 29 | 1.2830 | 0.5415 |
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| 1.1852 | 2.97 | 43 | 1.0794 | 0.5415 |
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| 1.1132 | 4.0 | 58 | 0.9314 | 0.6488 |
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| 0.9416 | 4.97 | 72 | 0.8935 | 0.6341 |
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| 0.9143 | 6.0 | 87 | 0.8009 | 0.6829 |
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| 0.8243 | 6.97 | 101 | 0.8067 | 0.6634 |
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| 0.8171 | 8.0 | 116 | 0.7783 | 0.6780 |
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| 0.7901 | 8.97 | 130 | 0.7871 | 0.6585 |
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| 0.7944 | 10.0 | 145 | 0.7414 | 0.6976 |
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| 0.7669 | 10.97 | 159 | 0.6977 | 0.7122 |
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| 0.7478 | 12.0 | 174 | 0.7043 | 0.7122 |
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| 0.766 | 12.97 | 188 | 0.7778 | 0.6585 |
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| 0.7322 | 14.0 | 203 | 0.7504 | 0.6780 |
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| 0.7242 | 14.97 | 217 | 0.7291 | 0.6829 |
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| 0.7554 | 16.0 | 232 | 0.7694 | 0.6634 |
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| 0.7422 | 16.97 | 246 | 0.7569 | 0.6829 |
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| 0.7292 | 18.0 | 261 | 0.7389 | 0.6780 |
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| 0.7354 | 18.97 | 275 | 0.6684 | 0.7122 |
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| 0.6847 | 20.0 | 290 | 0.6821 | 0.7122 |
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| 0.7231 | 20.97 | 304 | 0.6839 | 0.7024 |
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| 0.6962 | 22.0 | 319 | 0.6958 | 0.6878 |
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| 0.7079 | 22.97 | 333 | 0.7039 | 0.6878 |
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| 0.7088 | 24.0 | 348 | 0.6974 | 0.6878 |
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| 0.7106 | 24.14 | 350 | 0.6975 | 0.6878 |
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### Framework versions
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