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metadata
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
  - image-classification
  - vision
  - generated_from_trainer
datasets:
  - generator
model-index:
  - name: swinv2-base-panorama-IQA
    results: []

swinv2-base-panorama-IQA

This model is a fine-tuned version of microsoft/swinv2-base-patch4-window8-256 on the isiqa-2019-hf dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0246
  • Srocc: 0.0896
  • Lcc: 0.1773

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 10
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50.0

Training results

Training Loss Epoch Step Validation Loss Srocc Lcc
No log 0.8571 3 0.2685 -0.1661 -0.1400
No log 2.0 7 0.0675 -0.2071 -0.1319
0.223 2.8571 10 0.1380 -0.1972 -0.1144
0.223 4.0 14 0.0639 -0.2362 -0.1162
0.223 4.8571 17 0.0601 -0.1760 -0.1097
0.0607 6.0 21 0.0627 -0.1290 -0.0852
0.0607 6.8571 24 0.0543 -0.1050 -0.0791
0.0607 8.0 28 0.0408 -0.0683 -0.0702
0.0212 8.8571 31 0.0419 -0.0692 -0.0567
0.0212 10.0 35 0.0343 -0.0370 -0.0274
0.0212 10.8571 38 0.0307 -0.0339 -0.0013
0.0168 12.0 42 0.0299 -0.0281 0.0233
0.0168 12.8571 45 0.0300 -0.0428 0.0326
0.0168 14.0 49 0.0286 -0.0238 0.0517
0.0143 14.8571 52 0.0283 -0.0186 0.0601
0.0143 16.0 56 0.0273 -0.0024 0.0868
0.0143 16.8571 59 0.0257 0.0283 0.1119
0.013 18.0 63 0.0247 0.0542 0.1404
0.013 18.8571 66 0.0247 0.0703 0.1533
0.0111 20.0 70 0.0246 0.0800 0.1670
0.0111 20.8571 73 0.0246 0.0896 0.1773
0.0111 22.0 77 0.0257 0.0998 0.1835
0.0104 22.8571 80 0.0255 0.1017 0.1943
0.0104 24.0 84 0.0255 0.1149 0.2085
0.0104 24.8571 87 0.0255 0.1245 0.2155
0.0088 26.0 91 0.0262 0.1319 0.2258

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1