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Aerial-Drone-Image-Segmentation

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Aerial-Drone-Image-Segmentation / README.md
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metadata
license: other
tags:
  - generated_from_trainer
base_model: nvidia/mit-b0
model-index:
  - name: Aerial-Drone-Image-Segmentation
    results: []

Aerial-Drone-Image-Segmentation

This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8852
  • Mean Iou: 0.2994
  • Mean Accuracy: 0.3923
  • Overall Accuracy: 0.7774

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: 5e-05
  • train_batch_size: 24
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy
2.7923 1.25 20 2.8338 0.0954 0.1626 0.5529
2.219 2.5 40 2.1391 0.1036 0.1666 0.5929
1.9451 3.75 60 1.7919 0.1154 0.1782 0.6129
1.7558 5.0 80 1.6767 0.1300 0.1961 0.6396
1.6381 6.25 100 1.5817 0.1383 0.2055 0.6550
1.5338 7.5 120 1.4816 0.1464 0.2140 0.6729
1.4478 8.75 140 1.4231 0.1529 0.2219 0.6823
1.361 10.0 160 1.3300 0.1637 0.2315 0.6975
1.306 11.25 180 1.3034 0.1737 0.2419 0.7060
1.2611 12.5 200 1.2692 0.1755 0.2450 0.7093
1.2317 13.75 220 1.2190 0.1821 0.2501 0.7145
1.1868 15.0 240 1.2063 0.1862 0.2539 0.7188
1.1628 16.25 260 1.1832 0.1909 0.2612 0.7234
1.1149 17.5 280 1.1368 0.2048 0.2739 0.7317
1.1009 18.75 300 1.1117 0.2232 0.2938 0.7387
1.0532 20.0 320 1.0923 0.2315 0.2997 0.7414
1.0464 21.25 340 1.0821 0.2408 0.3147 0.7480
1.0278 22.5 360 1.0541 0.2517 0.3277 0.7530
0.9945 23.75 380 1.0352 0.2612 0.3398 0.7573
0.9729 25.0 400 1.0207 0.2671 0.3511 0.7609
0.9527 26.25 420 1.0067 0.2684 0.3547 0.7609
0.9494 27.5 440 0.9870 0.2713 0.3548 0.7627
0.9287 28.75 460 0.9729 0.2745 0.3619 0.7640
0.9089 30.0 480 0.9561 0.2791 0.3640 0.7680
0.9064 31.25 500 0.9500 0.2799 0.3712 0.7672
0.8681 32.5 520 0.9397 0.2845 0.3749 0.7696
0.8677 33.75 540 0.9340 0.2835 0.3737 0.7692
0.8663 35.0 560 0.9243 0.2862 0.3755 0.7716
0.8629 36.25 580 0.9173 0.2869 0.3766 0.7719
0.8542 37.5 600 0.9112 0.2908 0.3810 0.7740
0.8391 38.75 620 0.9050 0.2904 0.3812 0.7734
0.8392 40.0 640 0.9027 0.2917 0.3818 0.7734
0.8306 41.25 660 0.8949 0.2941 0.3841 0.7755
0.8213 42.5 680 0.8936 0.2958 0.3875 0.7760
0.8406 43.75 700 0.8910 0.2964 0.3879 0.7763
0.8254 45.0 720 0.8889 0.2981 0.3897 0.7764
0.8202 46.25 740 0.8880 0.2985 0.3917 0.7767
0.8013 47.5 760 0.8891 0.2989 0.3923 0.7767
0.8188 48.75 780 0.8861 0.2994 0.3926 0.7772
0.8089 50.0 800 0.8852 0.2994 0.3923 0.7774

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2