End of training
Browse files- README.md +277 -0
- all_results.json +13 -0
- config.json +63 -0
- eval_results.json +8 -0
- preprocessor_config.json +22 -0
- pytorch_model.bin +3 -0
- train_results.json +8 -0
- trainer_state.json +2068 -0
- training_args.bin +3 -0
README.md
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1 |
+
---
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2 |
+
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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9 |
+
- accuracy
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+
model-index:
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+
- name: swin-tiny-patch4-window7-224-finetuned-ADC-3cls-0922
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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: test
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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: 0.8142857142857143
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+
---
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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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+
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+
# swin-tiny-patch4-window7-224-finetuned-ADC-3cls-0922
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+
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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: 0.6875
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+
- Accuracy: 0.8143
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+
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+
## Model description
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+
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More information needed
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+
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## Intended uses & limitations
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+
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+
More information needed
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+
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## Training and evaluation data
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+
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+
More information needed
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+
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+
## Training procedure
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+
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+
### Training hyperparameters
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+
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+
The following hyperparameters were used during training:
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+
- learning_rate: 0.0001
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+
- train_batch_size: 64
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+
- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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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: 0.2
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- num_epochs: 200
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+
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+
### Training results
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+
|
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+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 2 | 1.0694 | 0.4143 |
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| No log | 2.0 | 4 | 1.0689 | 0.4143 |
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| No log | 3.0 | 6 | 1.0682 | 0.4143 |
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| No log | 4.0 | 8 | 1.0671 | 0.4143 |
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+
| 1.096 | 5.0 | 10 | 1.0657 | 0.4286 |
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+
| 1.096 | 6.0 | 12 | 1.0640 | 0.4286 |
|
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+
| 1.096 | 7.0 | 14 | 1.0621 | 0.4143 |
|
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| 1.096 | 8.0 | 16 | 1.0598 | 0.4 |
|
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| 1.096 | 9.0 | 18 | 1.0572 | 0.4 |
|
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| 1.0906 | 10.0 | 20 | 1.0545 | 0.4 |
|
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| 1.0906 | 11.0 | 22 | 1.0517 | 0.4143 |
|
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+
| 1.0906 | 12.0 | 24 | 1.0486 | 0.4143 |
|
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| 1.0906 | 13.0 | 26 | 1.0453 | 0.4143 |
|
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| 1.0906 | 14.0 | 28 | 1.0418 | 0.4143 |
|
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+
| 1.0647 | 15.0 | 30 | 1.0380 | 0.4143 |
|
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| 1.0647 | 16.0 | 32 | 1.0343 | 0.4143 |
|
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| 1.0647 | 17.0 | 34 | 1.0307 | 0.4143 |
|
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| 1.0647 | 18.0 | 36 | 1.0268 | 0.4286 |
|
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+
| 1.0647 | 19.0 | 38 | 1.0229 | 0.4286 |
|
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| 1.0451 | 20.0 | 40 | 1.0191 | 0.4429 |
|
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| 1.0451 | 21.0 | 42 | 1.0153 | 0.4571 |
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| 1.0451 | 22.0 | 44 | 1.0116 | 0.4714 |
|
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| 1.0451 | 23.0 | 46 | 1.0082 | 0.4714 |
|
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| 1.0451 | 24.0 | 48 | 1.0049 | 0.4714 |
|
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| 1.037 | 25.0 | 50 | 1.0016 | 0.4714 |
|
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| 1.037 | 26.0 | 52 | 0.9979 | 0.4714 |
|
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| 1.037 | 27.0 | 54 | 0.9944 | 0.4714 |
|
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| 1.037 | 28.0 | 56 | 0.9913 | 0.4714 |
|
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| 1.037 | 29.0 | 58 | 0.9883 | 0.4714 |
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| 1.0214 | 30.0 | 60 | 0.9847 | 0.4714 |
|
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| 1.0214 | 31.0 | 62 | 0.9809 | 0.4571 |
|
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| 1.0214 | 32.0 | 64 | 0.9768 | 0.4714 |
|
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| 1.0214 | 33.0 | 66 | 0.9723 | 0.4714 |
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| 1.0214 | 34.0 | 68 | 0.9671 | 0.4714 |
|
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| 1.0181 | 35.0 | 70 | 0.9616 | 0.4714 |
|
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| 1.0181 | 36.0 | 72 | 0.9561 | 0.4857 |
|
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| 1.0181 | 37.0 | 74 | 0.9505 | 0.5 |
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| 1.0181 | 38.0 | 76 | 0.9446 | 0.5286 |
|
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| 1.0181 | 39.0 | 78 | 0.9388 | 0.5286 |
|
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| 0.9646 | 40.0 | 80 | 0.9331 | 0.5286 |
|
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| 0.9646 | 41.0 | 82 | 0.9276 | 0.5143 |
|
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| 0.9646 | 42.0 | 84 | 0.9224 | 0.5286 |
|
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| 0.9646 | 43.0 | 86 | 0.9172 | 0.5286 |
|
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| 0.9646 | 44.0 | 88 | 0.9120 | 0.5286 |
|
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| 0.946 | 45.0 | 90 | 0.9070 | 0.5143 |
|
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| 0.946 | 46.0 | 92 | 0.9021 | 0.5286 |
|
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| 0.946 | 47.0 | 94 | 0.8976 | 0.5429 |
|
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| 0.946 | 48.0 | 96 | 0.8933 | 0.5429 |
|
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| 0.946 | 49.0 | 98 | 0.8891 | 0.5714 |
|
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| 0.9244 | 50.0 | 100 | 0.8846 | 0.5714 |
|
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| 0.9244 | 51.0 | 102 | 0.8803 | 0.5714 |
|
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| 0.9244 | 52.0 | 104 | 0.8759 | 0.5714 |
|
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| 0.9244 | 53.0 | 106 | 0.8716 | 0.5714 |
|
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| 0.9244 | 54.0 | 108 | 0.8674 | 0.5714 |
|
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| 0.9228 | 55.0 | 110 | 0.8634 | 0.5857 |
|
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| 0.9228 | 56.0 | 112 | 0.8598 | 0.6 |
|
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| 0.9228 | 57.0 | 114 | 0.8562 | 0.5857 |
|
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| 0.9228 | 58.0 | 116 | 0.8527 | 0.6 |
|
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| 0.9228 | 59.0 | 118 | 0.8492 | 0.6 |
|
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| 0.8956 | 60.0 | 120 | 0.8456 | 0.6143 |
|
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| 0.8956 | 61.0 | 122 | 0.8421 | 0.6 |
|
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| 0.8956 | 62.0 | 124 | 0.8385 | 0.6 |
|
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| 0.8956 | 63.0 | 126 | 0.8351 | 0.6 |
|
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| 0.8956 | 64.0 | 128 | 0.8318 | 0.6143 |
|
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| 0.8943 | 65.0 | 130 | 0.8286 | 0.6143 |
|
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| 0.8943 | 66.0 | 132 | 0.8255 | 0.6 |
|
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| 0.8943 | 67.0 | 134 | 0.8223 | 0.6286 |
|
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| 0.8943 | 68.0 | 136 | 0.8191 | 0.6429 |
|
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| 0.8943 | 69.0 | 138 | 0.8159 | 0.6286 |
|
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| 0.854 | 70.0 | 140 | 0.8129 | 0.6429 |
|
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| 0.854 | 71.0 | 142 | 0.8100 | 0.6714 |
|
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| 0.854 | 72.0 | 144 | 0.8073 | 0.6714 |
|
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| 0.854 | 73.0 | 146 | 0.8048 | 0.6571 |
|
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| 0.854 | 74.0 | 148 | 0.8025 | 0.6714 |
|
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| 0.8615 | 75.0 | 150 | 0.8001 | 0.6571 |
|
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| 0.8615 | 76.0 | 152 | 0.7976 | 0.6571 |
|
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| 0.8615 | 77.0 | 154 | 0.7952 | 0.6571 |
|
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| 0.8615 | 78.0 | 156 | 0.7928 | 0.6571 |
|
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| 0.8615 | 79.0 | 158 | 0.7904 | 0.6571 |
|
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| 0.8507 | 80.0 | 160 | 0.7882 | 0.6714 |
|
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| 0.8507 | 81.0 | 162 | 0.7858 | 0.6714 |
|
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| 0.8507 | 82.0 | 164 | 0.7835 | 0.6857 |
|
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| 0.8507 | 83.0 | 166 | 0.7811 | 0.6857 |
|
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| 0.8507 | 84.0 | 168 | 0.7788 | 0.6857 |
|
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| 0.838 | 85.0 | 170 | 0.7765 | 0.6857 |
|
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| 0.838 | 86.0 | 172 | 0.7743 | 0.6857 |
|
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| 0.838 | 87.0 | 174 | 0.7723 | 0.6857 |
|
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| 0.838 | 88.0 | 176 | 0.7703 | 0.6857 |
|
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| 0.838 | 89.0 | 178 | 0.7684 | 0.6857 |
|
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| 0.8245 | 90.0 | 180 | 0.7664 | 0.6857 |
|
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| 0.8245 | 91.0 | 182 | 0.7644 | 0.6857 |
|
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| 0.8245 | 92.0 | 184 | 0.7625 | 0.6857 |
|
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| 0.8245 | 93.0 | 186 | 0.7606 | 0.7143 |
|
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| 0.8245 | 94.0 | 188 | 0.7587 | 0.7143 |
|
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| 0.8124 | 95.0 | 190 | 0.7569 | 0.7143 |
|
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| 0.8124 | 96.0 | 192 | 0.7551 | 0.7286 |
|
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| 0.8124 | 97.0 | 194 | 0.7533 | 0.7286 |
|
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| 0.8124 | 98.0 | 196 | 0.7517 | 0.7286 |
|
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| 0.8124 | 99.0 | 198 | 0.7500 | 0.7429 |
|
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| 0.8102 | 100.0 | 200 | 0.7483 | 0.7429 |
|
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| 0.8102 | 101.0 | 202 | 0.7465 | 0.7429 |
|
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| 0.8102 | 102.0 | 204 | 0.7450 | 0.7429 |
|
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| 0.8102 | 103.0 | 206 | 0.7434 | 0.7429 |
|
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| 0.8102 | 104.0 | 208 | 0.7419 | 0.7429 |
|
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| 0.821 | 105.0 | 210 | 0.7404 | 0.7571 |
|
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| 0.821 | 106.0 | 212 | 0.7389 | 0.7571 |
|
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| 0.821 | 107.0 | 214 | 0.7374 | 0.7571 |
|
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| 0.821 | 108.0 | 216 | 0.7359 | 0.7571 |
|
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| 0.821 | 109.0 | 218 | 0.7345 | 0.7571 |
|
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| 0.7918 | 110.0 | 220 | 0.7330 | 0.7571 |
|
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| 0.7918 | 111.0 | 222 | 0.7316 | 0.7571 |
|
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| 0.7918 | 112.0 | 224 | 0.7302 | 0.7571 |
|
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| 0.7918 | 113.0 | 226 | 0.7289 | 0.7571 |
|
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| 0.7918 | 114.0 | 228 | 0.7275 | 0.7571 |
|
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| 0.8063 | 115.0 | 230 | 0.7262 | 0.7714 |
|
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| 0.8063 | 116.0 | 232 | 0.7247 | 0.7714 |
|
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| 0.8063 | 117.0 | 234 | 0.7232 | 0.7571 |
|
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| 0.8063 | 118.0 | 236 | 0.7218 | 0.7571 |
|
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| 0.8063 | 119.0 | 238 | 0.7204 | 0.7571 |
|
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| 0.7897 | 120.0 | 240 | 0.7192 | 0.7571 |
|
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| 0.7897 | 121.0 | 242 | 0.7180 | 0.7571 |
|
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| 0.7897 | 122.0 | 244 | 0.7168 | 0.7571 |
|
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| 0.7897 | 123.0 | 246 | 0.7158 | 0.7571 |
|
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| 0.7897 | 124.0 | 248 | 0.7149 | 0.7714 |
|
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| 0.7845 | 125.0 | 250 | 0.7140 | 0.7571 |
|
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| 0.7845 | 126.0 | 252 | 0.7131 | 0.7571 |
|
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| 0.7845 | 127.0 | 254 | 0.7121 | 0.7571 |
|
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| 0.7845 | 128.0 | 256 | 0.7110 | 0.7571 |
|
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| 0.7845 | 129.0 | 258 | 0.7099 | 0.7571 |
|
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| 0.7781 | 130.0 | 260 | 0.7088 | 0.7571 |
|
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| 0.7781 | 131.0 | 262 | 0.7076 | 0.7571 |
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| 0.7781 | 132.0 | 264 | 0.7066 | 0.7571 |
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| 0.7781 | 133.0 | 266 | 0.7055 | 0.7571 |
|
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| 0.7781 | 134.0 | 268 | 0.7045 | 0.7714 |
|
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| 0.7708 | 135.0 | 270 | 0.7034 | 0.7714 |
|
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| 0.7708 | 136.0 | 272 | 0.7025 | 0.7571 |
|
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| 0.7708 | 137.0 | 274 | 0.7016 | 0.7571 |
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| 0.7708 | 138.0 | 276 | 0.7008 | 0.7571 |
|
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| 0.7708 | 139.0 | 278 | 0.6999 | 0.7571 |
|
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| 0.797 | 140.0 | 280 | 0.6990 | 0.7571 |
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| 0.797 | 141.0 | 282 | 0.6981 | 0.7714 |
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| 0.797 | 142.0 | 284 | 0.6973 | 0.7714 |
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| 0.797 | 143.0 | 286 | 0.6966 | 0.7714 |
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| 0.797 | 144.0 | 288 | 0.6959 | 0.7714 |
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| 0.7768 | 145.0 | 290 | 0.6952 | 0.7714 |
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| 0.7768 | 146.0 | 292 | 0.6944 | 0.7714 |
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| 0.7768 | 147.0 | 294 | 0.6936 | 0.7714 |
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| 0.7768 | 148.0 | 296 | 0.6928 | 0.7857 |
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| 0.7768 | 149.0 | 298 | 0.6920 | 0.7857 |
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| 0.7569 | 150.0 | 300 | 0.6912 | 0.7857 |
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| 0.7569 | 151.0 | 302 | 0.6904 | 0.8 |
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| 0.7569 | 152.0 | 304 | 0.6897 | 0.8 |
|
222 |
+
| 0.7569 | 153.0 | 306 | 0.6890 | 0.8 |
|
223 |
+
| 0.7569 | 154.0 | 308 | 0.6882 | 0.8 |
|
224 |
+
| 0.7807 | 155.0 | 310 | 0.6875 | 0.8143 |
|
225 |
+
| 0.7807 | 156.0 | 312 | 0.6868 | 0.8143 |
|
226 |
+
| 0.7807 | 157.0 | 314 | 0.6861 | 0.8143 |
|
227 |
+
| 0.7807 | 158.0 | 316 | 0.6854 | 0.8143 |
|
228 |
+
| 0.7807 | 159.0 | 318 | 0.6848 | 0.8143 |
|
229 |
+
| 0.7472 | 160.0 | 320 | 0.6842 | 0.8143 |
|
230 |
+
| 0.7472 | 161.0 | 322 | 0.6836 | 0.8143 |
|
231 |
+
| 0.7472 | 162.0 | 324 | 0.6831 | 0.8143 |
|
232 |
+
| 0.7472 | 163.0 | 326 | 0.6826 | 0.8143 |
|
233 |
+
| 0.7472 | 164.0 | 328 | 0.6822 | 0.8143 |
|
234 |
+
| 0.7665 | 165.0 | 330 | 0.6818 | 0.8 |
|
235 |
+
| 0.7665 | 166.0 | 332 | 0.6814 | 0.8 |
|
236 |
+
| 0.7665 | 167.0 | 334 | 0.6810 | 0.8 |
|
237 |
+
| 0.7665 | 168.0 | 336 | 0.6807 | 0.7857 |
|
238 |
+
| 0.7665 | 169.0 | 338 | 0.6803 | 0.7857 |
|
239 |
+
| 0.7684 | 170.0 | 340 | 0.6800 | 0.7857 |
|
240 |
+
| 0.7684 | 171.0 | 342 | 0.6797 | 0.7857 |
|
241 |
+
| 0.7684 | 172.0 | 344 | 0.6794 | 0.7857 |
|
242 |
+
| 0.7684 | 173.0 | 346 | 0.6790 | 0.7857 |
|
243 |
+
| 0.7684 | 174.0 | 348 | 0.6787 | 0.7857 |
|
244 |
+
| 0.7459 | 175.0 | 350 | 0.6784 | 0.7857 |
|
245 |
+
| 0.7459 | 176.0 | 352 | 0.6781 | 0.7857 |
|
246 |
+
| 0.7459 | 177.0 | 354 | 0.6778 | 0.7857 |
|
247 |
+
| 0.7459 | 178.0 | 356 | 0.6775 | 0.7857 |
|
248 |
+
| 0.7459 | 179.0 | 358 | 0.6772 | 0.7857 |
|
249 |
+
| 0.742 | 180.0 | 360 | 0.6769 | 0.7857 |
|
250 |
+
| 0.742 | 181.0 | 362 | 0.6766 | 0.7857 |
|
251 |
+
| 0.742 | 182.0 | 364 | 0.6764 | 0.7857 |
|
252 |
+
| 0.742 | 183.0 | 366 | 0.6762 | 0.7857 |
|
253 |
+
| 0.742 | 184.0 | 368 | 0.6760 | 0.7857 |
|
254 |
+
| 0.7642 | 185.0 | 370 | 0.6758 | 0.7857 |
|
255 |
+
| 0.7642 | 186.0 | 372 | 0.6756 | 0.7857 |
|
256 |
+
| 0.7642 | 187.0 | 374 | 0.6754 | 0.7857 |
|
257 |
+
| 0.7642 | 188.0 | 376 | 0.6752 | 0.7857 |
|
258 |
+
| 0.7642 | 189.0 | 378 | 0.6750 | 0.7857 |
|
259 |
+
| 0.7277 | 190.0 | 380 | 0.6749 | 0.7857 |
|
260 |
+
| 0.7277 | 191.0 | 382 | 0.6748 | 0.7857 |
|
261 |
+
| 0.7277 | 192.0 | 384 | 0.6746 | 0.7857 |
|
262 |
+
| 0.7277 | 193.0 | 386 | 0.6745 | 0.7857 |
|
263 |
+
| 0.7277 | 194.0 | 388 | 0.6745 | 0.7857 |
|
264 |
+
| 0.764 | 195.0 | 390 | 0.6744 | 0.7857 |
|
265 |
+
| 0.764 | 196.0 | 392 | 0.6743 | 0.7857 |
|
266 |
+
| 0.764 | 197.0 | 394 | 0.6742 | 0.7857 |
|
267 |
+
| 0.764 | 198.0 | 396 | 0.6742 | 0.8 |
|
268 |
+
| 0.764 | 199.0 | 398 | 0.6742 | 0.8 |
|
269 |
+
| 0.7444 | 200.0 | 400 | 0.6742 | 0.8 |
|
270 |
+
|
271 |
+
|
272 |
+
### Framework versions
|
273 |
+
|
274 |
+
- Transformers 4.33.2
|
275 |
+
- Pytorch 2.0.1+cu118
|
276 |
+
- Datasets 2.14.5
|
277 |
+
- Tokenizers 0.13.3
|
all_results.json
ADDED
@@ -0,0 +1,13 @@
|
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|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 200.0,
|
3 |
+
"eval_accuracy": 0.8142857142857143,
|
4 |
+
"eval_loss": 0.6875176429748535,
|
5 |
+
"eval_runtime": 0.839,
|
6 |
+
"eval_samples_per_second": 83.432,
|
7 |
+
"eval_steps_per_second": 2.384,
|
8 |
+
"total_flos": 2.23710151698432e+18,
|
9 |
+
"train_loss": 0.8548950719833374,
|
10 |
+
"train_runtime": 1030.1946,
|
11 |
+
"train_samples_per_second": 87.362,
|
12 |
+
"train_steps_per_second": 0.388
|
13 |
+
}
|
config.json
ADDED
@@ -0,0 +1,63 @@
|
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|
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|
1 |
+
{
|
2 |
+
"_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
|
3 |
+
"architectures": [
|
4 |
+
"SwinForImageClassification"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.0,
|
7 |
+
"depths": [
|
8 |
+
2,
|
9 |
+
2,
|
10 |
+
6,
|
11 |
+
2
|
12 |
+
],
|
13 |
+
"drop_path_rate": 0.1,
|
14 |
+
"embed_dim": 96,
|
15 |
+
"encoder_stride": 32,
|
16 |
+
"hidden_act": "gelu",
|
17 |
+
"hidden_dropout_prob": 0.0,
|
18 |
+
"hidden_size": 768,
|
19 |
+
"id2label": {
|
20 |
+
"0": "Color",
|
21 |
+
"1": "Pattern_fail",
|
22 |
+
"2": "Residue"
|
23 |
+
},
|
24 |
+
"image_size": 224,
|
25 |
+
"initializer_range": 0.02,
|
26 |
+
"label2id": {
|
27 |
+
"Color": 0,
|
28 |
+
"Pattern_fail": 1,
|
29 |
+
"Residue": 2
|
30 |
+
},
|
31 |
+
"layer_norm_eps": 1e-05,
|
32 |
+
"mlp_ratio": 4.0,
|
33 |
+
"model_type": "swin",
|
34 |
+
"num_channels": 3,
|
35 |
+
"num_heads": [
|
36 |
+
3,
|
37 |
+
6,
|
38 |
+
12,
|
39 |
+
24
|
40 |
+
],
|
41 |
+
"num_layers": 4,
|
42 |
+
"out_features": [
|
43 |
+
"stage4"
|
44 |
+
],
|
45 |
+
"out_indices": [
|
46 |
+
4
|
47 |
+
],
|
48 |
+
"patch_size": 4,
|
49 |
+
"path_norm": true,
|
50 |
+
"problem_type": "single_label_classification",
|
51 |
+
"qkv_bias": true,
|
52 |
+
"stage_names": [
|
53 |
+
"stem",
|
54 |
+
"stage1",
|
55 |
+
"stage2",
|
56 |
+
"stage3",
|
57 |
+
"stage4"
|
58 |
+
],
|
59 |
+
"torch_dtype": "float32",
|
60 |
+
"transformers_version": "4.33.2",
|
61 |
+
"use_absolute_embeddings": false,
|
62 |
+
"window_size": 7
|
63 |
+
}
|
eval_results.json
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 200.0,
|
3 |
+
"eval_accuracy": 0.8142857142857143,
|
4 |
+
"eval_loss": 0.6875176429748535,
|
5 |
+
"eval_runtime": 0.839,
|
6 |
+
"eval_samples_per_second": 83.432,
|
7 |
+
"eval_steps_per_second": 2.384
|
8 |
+
}
|
preprocessor_config.json
ADDED
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"do_normalize": true,
|
3 |
+
"do_rescale": true,
|
4 |
+
"do_resize": true,
|
5 |
+
"image_mean": [
|
6 |
+
0.485,
|
7 |
+
0.456,
|
8 |
+
0.406
|
9 |
+
],
|
10 |
+
"image_processor_type": "ViTImageProcessor",
|
11 |
+
"image_std": [
|
12 |
+
0.229,
|
13 |
+
0.224,
|
14 |
+
0.225
|
15 |
+
],
|
16 |
+
"resample": 3,
|
17 |
+
"rescale_factor": 0.00392156862745098,
|
18 |
+
"size": {
|
19 |
+
"height": 224,
|
20 |
+
"width": 224
|
21 |
+
}
|
22 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b62d9ef2983c93a25662930965516fed575d4b4bf9ef9e40f118fd77873bd11f
|
3 |
+
size 110397937
|
train_results.json
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 200.0,
|
3 |
+
"total_flos": 2.23710151698432e+18,
|
4 |
+
"train_loss": 0.8548950719833374,
|
5 |
+
"train_runtime": 1030.1946,
|
6 |
+
"train_samples_per_second": 87.362,
|
7 |
+
"train_steps_per_second": 0.388
|
8 |
+
}
|
trainer_state.json
ADDED
@@ -0,0 +1,2068 @@
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training_args.bin
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@@ -0,0 +1,3 @@
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