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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft |
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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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datasets: |
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- generator |
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model-index: |
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- name: swinv2-large-panorama-IQA |
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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-large-panorama-IQA |
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This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the isiqa-2019-hf dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0352 |
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- Srocc: 0.0683 |
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- Lcc: 0.1820 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 32 |
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- seed: 10 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Srocc | Lcc | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:| |
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| No log | 0.8889 | 3 | 0.4401 | -0.1586 | -0.1147 | |
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| No log | 1.7778 | 6 | 0.2206 | -0.2675 | -0.1545 | |
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| 0.3084 | 2.9630 | 10 | 0.1910 | -0.2754 | -0.1813 | |
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| 0.3084 | 3.8519 | 13 | 0.2334 | -0.2170 | -0.1511 | |
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| 0.3084 | 4.7407 | 16 | 0.1484 | -0.2 | -0.1310 | |
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| 0.0852 | 5.9259 | 20 | 0.1259 | -0.1021 | -0.0852 | |
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| 0.0852 | 6.8148 | 23 | 0.1552 | -0.0709 | -0.0595 | |
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| 0.0852 | 8.0 | 27 | 0.0942 | -0.0948 | -0.0584 | |
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| 0.0406 | 8.8889 | 30 | 0.0841 | -0.0480 | -0.0550 | |
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| 0.0406 | 9.7778 | 33 | 0.0886 | -0.0576 | -0.0448 | |
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| 0.0406 | 10.9630 | 37 | 0.0721 | -0.0773 | -0.0474 | |
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| 0.023 | 11.8519 | 40 | 0.0697 | -0.0446 | -0.0364 | |
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| 0.023 | 12.7407 | 43 | 0.0577 | -0.0217 | -0.0091 | |
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| 0.023 | 13.9259 | 47 | 0.0666 | -0.0314 | 0.0112 | |
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| 0.0136 | 14.8148 | 50 | 0.0525 | -0.0501 | 0.0060 | |
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| 0.0136 | 16.0 | 54 | 0.0626 | -0.0178 | 0.0504 | |
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| 0.0136 | 16.8889 | 57 | 0.0438 | 0.0159 | 0.0827 | |
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| 0.0113 | 17.7778 | 60 | 0.0503 | 0.0741 | 0.1074 | |
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| 0.0113 | 18.9630 | 64 | 0.0429 | 0.0818 | 0.1129 | |
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| 0.0113 | 19.8519 | 67 | 0.0455 | 0.0874 | 0.1188 | |
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| 0.0097 | 20.7407 | 70 | 0.0597 | 0.0926 | 0.1316 | |
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| 0.0097 | 21.9259 | 74 | 0.0397 | 0.0614 | 0.1446 | |
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| 0.0097 | 22.8148 | 77 | 0.0529 | 0.0778 | 0.1637 | |
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| 0.0084 | 24.0 | 81 | 0.0366 | 0.0716 | 0.1761 | |
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| 0.0084 | 24.8889 | 84 | 0.0352 | 0.0683 | 0.1820 | |
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| 0.0084 | 25.7778 | 87 | 0.0491 | 0.0970 | 0.1848 | |
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| 0.0078 | 26.9630 | 91 | 0.0396 | 0.0984 | 0.1831 | |
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| 0.0078 | 27.8519 | 94 | 0.0395 | 0.1012 | 0.1856 | |
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| 0.0078 | 28.7407 | 97 | 0.0426 | 0.1097 | 0.1956 | |
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| 0.0063 | 29.9259 | 101 | 0.0370 | 0.1002 | 0.1984 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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