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JCAI2000
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segformer-b0-finetuned-100by100PNG-50epochs-attempt2-100epochsNoReduce

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +158 -0
  2. config.json +76 -0
  3. pytorch_model.bin +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: other
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+ base_model: nvidia/mit-b0
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+ tags:
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+ - vision
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+ - image-segmentation
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b0-finetuned-100by100PNG-50epochs-attempt2-100epochsNoReduce
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+ results: []
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+ ---
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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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+
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+ # segformer-b0-finetuned-100by100PNG-50epochs-attempt2-100epochsNoReduce
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the JCAI2000/100By100BranchPNG dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2286
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+ - Mean Iou: 0.8224
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+ - Mean Accuracy: 1.0
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+ - Overall Accuracy: 1.0
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+ - Accuracy Branch: 1.0
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+ - Iou Branch: 0.8224
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Branch | Iou Branch |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------:|:----------:|
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+ | 0.5864 | 1.05 | 20 | 0.6005 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.4461 | 2.11 | 40 | 0.4242 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.2556 | 3.16 | 60 | 0.3245 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.234 | 4.21 | 80 | 0.3176 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1917 | 5.26 | 100 | 0.2751 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.2608 | 6.32 | 120 | 0.2997 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.2789 | 7.37 | 140 | 0.2508 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.2173 | 8.42 | 160 | 0.2684 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1552 | 9.47 | 180 | 0.2374 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1809 | 10.53 | 200 | 0.2596 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1342 | 11.58 | 220 | 0.2375 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1946 | 12.63 | 240 | 0.2211 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1215 | 13.68 | 260 | 0.2135 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1212 | 14.74 | 280 | 0.2470 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1536 | 15.79 | 300 | 0.2224 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1282 | 16.84 | 320 | 0.2466 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.11 | 17.89 | 340 | 0.2316 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1228 | 18.95 | 360 | 0.2233 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1243 | 20.0 | 380 | 0.1996 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0893 | 21.05 | 400 | 0.2074 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1012 | 22.11 | 420 | 0.1941 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1587 | 23.16 | 440 | 0.2007 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0913 | 24.21 | 460 | 0.2211 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0949 | 25.26 | 480 | 0.2621 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0863 | 26.32 | 500 | 0.2195 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.066 | 27.37 | 520 | 0.2221 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0738 | 28.42 | 540 | 0.2126 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0808 | 29.47 | 560 | 0.2068 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.062 | 30.53 | 580 | 0.2599 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0787 | 31.58 | 600 | 0.2366 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0535 | 32.63 | 620 | 0.2165 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0681 | 33.68 | 640 | 0.2212 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0574 | 34.74 | 660 | 0.2160 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.109 | 35.79 | 680 | 0.2281 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0702 | 36.84 | 700 | 0.2403 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0578 | 37.89 | 720 | 0.2141 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0643 | 38.95 | 740 | 0.2101 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0948 | 40.0 | 760 | 0.2118 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0453 | 41.05 | 780 | 0.2048 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0472 | 42.11 | 800 | 0.1924 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0699 | 43.16 | 820 | 0.2197 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0492 | 44.21 | 840 | 0.2172 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0888 | 45.26 | 860 | 0.2196 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0438 | 46.32 | 880 | 0.2196 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0524 | 47.37 | 900 | 0.2232 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0453 | 48.42 | 920 | 0.2184 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1319 | 49.47 | 940 | 0.2080 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0423 | 50.53 | 960 | 0.2180 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0592 | 51.58 | 980 | 0.2251 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0395 | 52.63 | 1000 | 0.2198 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0451 | 53.68 | 1020 | 0.1953 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0446 | 54.74 | 1040 | 0.2072 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.048 | 55.79 | 1060 | 0.2222 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0623 | 56.84 | 1080 | 0.2264 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0765 | 57.89 | 1100 | 0.2419 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0661 | 58.95 | 1120 | 0.2251 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0625 | 60.0 | 1140 | 0.2254 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0373 | 61.05 | 1160 | 0.2209 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0402 | 62.11 | 1180 | 0.2178 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0339 | 63.16 | 1200 | 0.2076 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0608 | 64.21 | 1220 | 0.2177 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0301 | 65.26 | 1240 | 0.2048 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0461 | 66.32 | 1260 | 0.2124 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0395 | 67.37 | 1280 | 0.2188 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.1034 | 68.42 | 1300 | 0.2251 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0368 | 69.47 | 1320 | 0.2169 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0501 | 70.53 | 1340 | 0.2180 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0417 | 71.58 | 1360 | 0.2255 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0351 | 72.63 | 1380 | 0.2154 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0423 | 73.68 | 1400 | 0.2216 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.032 | 74.74 | 1420 | 0.2211 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0586 | 75.79 | 1440 | 0.2144 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0315 | 76.84 | 1460 | 0.2166 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.039 | 77.89 | 1480 | 0.2258 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0838 | 78.95 | 1500 | 0.2290 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0543 | 80.0 | 1520 | 0.2414 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0444 | 81.05 | 1540 | 0.2240 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0501 | 82.11 | 1560 | 0.2253 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0275 | 83.16 | 1580 | 0.2190 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0356 | 84.21 | 1600 | 0.2188 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0378 | 85.26 | 1620 | 0.2214 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0306 | 86.32 | 1640 | 0.2195 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0348 | 87.37 | 1660 | 0.2172 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0363 | 88.42 | 1680 | 0.2180 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0454 | 89.47 | 1700 | 0.2234 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0367 | 90.53 | 1720 | 0.2224 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0265 | 91.58 | 1740 | 0.2308 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0404 | 92.63 | 1760 | 0.2269 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0335 | 93.68 | 1780 | 0.2229 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0292 | 94.74 | 1800 | 0.2269 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.041 | 95.79 | 1820 | 0.2277 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0325 | 96.84 | 1840 | 0.2225 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0371 | 97.89 | 1860 | 0.2250 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0336 | 98.95 | 1880 | 0.2259 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+ | 0.0445 | 100.0 | 1900 | 0.2286 | 0.8224 | 1.0 | 1.0 | 1.0 | 0.8224 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "nvidia/mit-b0",
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+ "architectures": [
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+ "SegformerForSemanticSegmentation"
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+ ],
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+ "classifier_dropout_prob": 0.1,
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+ ],
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+ "downsampling_rates": [
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+ 1,
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+ 4,
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+ 8,
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+ ],
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+ "drop_path_rate": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_sizes": [
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+ 32,
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+ 64,
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+ 160,
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+ 256
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+ ],
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+ "id2label": {
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+ "1": "branch"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "branch": 1
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
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+ ],
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+ "model_type": "segformer",
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+ "num_attention_heads": [
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+ 1,
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+ 2,
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+ 5,
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+ 8
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+ ],
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+ "num_channels": 3,
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+ "num_encoder_blocks": 4,
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+ "patch_sizes": [
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+ 7,
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+ 3,
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+ 3
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+ ],
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+ "reshape_last_stage": true,
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+ "semantic_loss_ignore_index": 255,
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+ "sr_ratios": [
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+ 8,
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+ 4,
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+ 1
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+ ],
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+ "strides": [
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+ 4,
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.0"
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+ }
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