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

swinv2-tiny-panorama-IQA

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

  • Loss: 0.0175
  • Srocc: 0.2288
  • Lcc: 0.4304

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: 32
  • eval_batch_size: 32
  • seed: 10
  • gradient_accumulation_steps: 2
  • 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 0.1484 0.1044 0.1970
No log 2.0 7 0.0292 0.1107 0.1713
0.1442 2.8571 10 0.0548 0.0279 0.1178
0.1442 4.0 14 0.0310 -0.0628 0.0689
0.1442 4.8571 17 0.0476 -0.0618 0.0550
0.0425 6.0 21 0.0297 -0.0978 0.0051
0.0425 6.8571 24 0.0259 -0.0906 -0.0039
0.0425 8.0 28 0.0294 -0.0270 0.0079
0.0242 8.8571 31 0.0237 -0.0146 0.0323
0.0242 10.0 35 0.0226 0.0152 0.0809
0.0242 10.8571 38 0.0236 0.0339 0.1158
0.0146 12.0 42 0.0213 0.0562 0.1753
0.0146 12.8571 45 0.0199 0.0678 0.2241
0.0146 14.0 49 0.0205 0.0981 0.2702
0.0116 14.8571 52 0.0190 0.1245 0.3000
0.0116 16.0 56 0.0195 0.1595 0.3511
0.0116 16.8571 59 0.0194 0.1829 0.3804
0.0096 18.0 63 0.0183 0.2144 0.4030
0.0096 18.8571 66 0.0195 0.2120 0.4086
0.0075 20.0 70 0.0188 0.2164 0.4127
0.0075 20.8571 73 0.0209 0.2222 0.4224
0.0075 22.0 77 0.0175 0.2288 0.4304
0.0076 22.8571 80 0.0211 0.2432 0.4326
0.0076 24.0 84 0.0189 0.2346 0.4327
0.0076 24.8571 87 0.0188 0.2294 0.4313
0.006 26.0 91 0.0223 0.2390 0.4343
0.006 26.8571 94 0.0202 0.2511 0.4399

Framework versions

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