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segformer-b0-finetuned-segments-sidewalk-2

Image Segmentation
Transformers
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
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segformer-b0-finetuned-segments-sidewalk-2 / README.md
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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-segments-sidewalk-2
    results: []

segformer-b0-finetuned-segments-sidewalk-2

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

  • Loss: 0.1287

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: 6e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 150

Training results

Training Loss Epoch Step Validation Loss
2.9957 2.8571 20 3.4269
2.6593 5.7143 40 2.3621
1.9746 8.5714 60 1.2378
1.5998 11.4286 80 1.2329
1.3299 14.2857 100 0.8019
1.3781 17.1429 120 0.8478
2.1912 20.0 140 0.6386
1.0362 22.8571 160 0.6467
1.3817 25.7143 180 0.4496
0.8108 28.5714 200 0.4032
0.8187 31.4286 220 0.4650
0.6671 34.2857 240 0.3251
0.6062 37.1429 260 0.4035
1.4152 40.0 280 0.3076
1.3078 42.8571 300 0.2517
0.4267 45.7143 320 0.2405
0.5829 48.5714 340 0.2142
0.8742 51.4286 360 0.2055
0.3055 54.2857 380 0.2257
0.5966 57.1429 400 0.1559
0.5006 60.0 420 0.1927
0.4433 62.8571 440 0.1525
0.2377 65.7143 460 0.1597
0.2612 68.5714 480 0.1703
0.477 71.4286 500 0.1663
0.2006 74.2857 520 0.1427
0.2641 77.1429 540 0.1370
0.5154 80.0 560 0.1386
0.447 82.8571 580 0.1274
0.195 85.7143 600 0.1236
0.1643 88.5714 620 0.1420
0.4199 91.4286 640 0.1226
0.1644 94.2857 660 0.1419
0.312 97.1429 680 0.1365
0.3905 100.0 700 0.1181
0.4035 102.8571 720 0.1305
0.1411 105.7143 740 0.1262
0.3018 108.5714 760 0.1322
0.1332 111.4286 780 0.1317
0.303 114.2857 800 0.1205
0.2399 117.1429 820 0.1358
0.2488 120.0 840 0.1226
0.304 122.8571 860 0.1275
0.2278 125.7143 880 0.1280
0.2718 128.5714 900 0.1294
0.5304 131.4286 920 0.1320
0.1143 134.2857 940 0.1279
0.1075 137.1429 960 0.1258
0.2103 140.0 980 0.1349
0.1483 142.8571 1000 0.1230
0.287 145.7143 1020 0.1253
0.3606 148.5714 1040 0.1287

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cpu
  • Datasets 2.19.2
  • Tokenizers 0.19.1