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--- |
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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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- 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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<!-- 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-finetuned-ADC-3cls-0922 |
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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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## 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: 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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### 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 | 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 | |
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| 0.7569 | 153.0 | 306 | 0.6890 | 0.8 | |
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| 0.7569 | 154.0 | 308 | 0.6882 | 0.8 | |
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| 0.7807 | 155.0 | 310 | 0.6875 | 0.8143 | |
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| 0.7807 | 156.0 | 312 | 0.6868 | 0.8143 | |
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| 0.7807 | 157.0 | 314 | 0.6861 | 0.8143 | |
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| 0.7807 | 158.0 | 316 | 0.6854 | 0.8143 | |
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| 0.7807 | 159.0 | 318 | 0.6848 | 0.8143 | |
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| 0.7472 | 160.0 | 320 | 0.6842 | 0.8143 | |
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| 0.7472 | 161.0 | 322 | 0.6836 | 0.8143 | |
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| 0.7472 | 162.0 | 324 | 0.6831 | 0.8143 | |
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| 0.7472 | 163.0 | 326 | 0.6826 | 0.8143 | |
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| 0.7472 | 164.0 | 328 | 0.6822 | 0.8143 | |
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| 0.7665 | 165.0 | 330 | 0.6818 | 0.8 | |
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| 0.7665 | 166.0 | 332 | 0.6814 | 0.8 | |
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| 0.7665 | 167.0 | 334 | 0.6810 | 0.8 | |
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| 0.7665 | 168.0 | 336 | 0.6807 | 0.7857 | |
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| 0.7665 | 169.0 | 338 | 0.6803 | 0.7857 | |
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| 0.7684 | 170.0 | 340 | 0.6800 | 0.7857 | |
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| 0.7684 | 171.0 | 342 | 0.6797 | 0.7857 | |
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| 0.7684 | 172.0 | 344 | 0.6794 | 0.7857 | |
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| 0.7684 | 173.0 | 346 | 0.6790 | 0.7857 | |
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| 0.7684 | 174.0 | 348 | 0.6787 | 0.7857 | |
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| 0.7459 | 175.0 | 350 | 0.6784 | 0.7857 | |
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| 0.7459 | 176.0 | 352 | 0.6781 | 0.7857 | |
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| 0.7459 | 177.0 | 354 | 0.6778 | 0.7857 | |
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| 0.7459 | 178.0 | 356 | 0.6775 | 0.7857 | |
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| 0.7459 | 179.0 | 358 | 0.6772 | 0.7857 | |
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| 0.742 | 180.0 | 360 | 0.6769 | 0.7857 | |
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| 0.742 | 181.0 | 362 | 0.6766 | 0.7857 | |
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| 0.742 | 182.0 | 364 | 0.6764 | 0.7857 | |
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| 0.742 | 183.0 | 366 | 0.6762 | 0.7857 | |
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| 0.742 | 184.0 | 368 | 0.6760 | 0.7857 | |
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| 0.7642 | 185.0 | 370 | 0.6758 | 0.7857 | |
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| 0.7642 | 186.0 | 372 | 0.6756 | 0.7857 | |
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| 0.7642 | 187.0 | 374 | 0.6754 | 0.7857 | |
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| 0.7642 | 188.0 | 376 | 0.6752 | 0.7857 | |
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| 0.7642 | 189.0 | 378 | 0.6750 | 0.7857 | |
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| 0.7277 | 190.0 | 380 | 0.6749 | 0.7857 | |
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| 0.7277 | 191.0 | 382 | 0.6748 | 0.7857 | |
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| 0.7277 | 192.0 | 384 | 0.6746 | 0.7857 | |
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| 0.7277 | 193.0 | 386 | 0.6745 | 0.7857 | |
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| 0.7277 | 194.0 | 388 | 0.6745 | 0.7857 | |
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| 0.764 | 195.0 | 390 | 0.6744 | 0.7857 | |
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| 0.764 | 196.0 | 392 | 0.6743 | 0.7857 | |
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| 0.764 | 197.0 | 394 | 0.6742 | 0.7857 | |
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| 0.764 | 198.0 | 396 | 0.6742 | 0.8 | |
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| 0.764 | 199.0 | 398 | 0.6742 | 0.8 | |
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| 0.7444 | 200.0 | 400 | 0.6742 | 0.8 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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