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End of training

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  1. README.md +50 -0
  2. config.json +144 -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-b5
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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-segments-sidewalk-2
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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-segments-sidewalk-2
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+
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+ This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the segments/sidewalk-semantic dataset.
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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: 50
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "nvidia/mit-b5",
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+ "architectures": [
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+ "SegformerForSemanticSegmentation"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "classifier_dropout_prob": 0.1,
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+ "decoder_hidden_size": 768,
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+ "depths": [
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+ 3,
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+ 6,
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+ 40,
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+ 3
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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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+ 16
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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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+ 64,
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+ 128,
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+ 320,
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+ 512
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+ ],
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+ "id2label": {
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+ "0": "unlabeled",
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+ "1": "flat-road",
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+ "2": "flat-sidewalk",
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+ "3": "flat-crosswalk",
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+ "4": "flat-cyclinglane",
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+ "5": "flat-parkingdriveway",
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+ "6": "flat-railtrack",
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+ "7": "flat-curb",
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+ "8": "human-person",
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+ "9": "human-rider",
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+ "10": "vehicle-car",
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+ "11": "vehicle-truck",
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+ "12": "vehicle-bus",
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+ "13": "vehicle-tramtrain",
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+ "14": "vehicle-motorcycle",
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+ "15": "vehicle-bicycle",
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+ "16": "vehicle-caravan",
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+ "17": "vehicle-cartrailer",
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+ "18": "construction-building",
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+ "19": "construction-door",
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+ "20": "construction-wall",
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+ "21": "construction-fenceguardrail",
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+ "22": "construction-bridge",
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+ "23": "construction-tunnel",
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+ "24": "construction-stairs",
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+ "25": "object-pole",
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+ "26": "object-trafficsign",
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+ "27": "object-trafficlight",
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+ "28": "nature-vegetation",
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+ "29": "nature-terrain",
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+ "30": "sky",
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+ "31": "void-ground",
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+ "32": "void-dynamic",
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+ "33": "void-static",
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+ "34": "void-unclear"
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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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+ "construction-bridge": 22,
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+ "construction-building": 18,
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+ "construction-door": 19,
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+ "construction-fenceguardrail": 21,
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+ "construction-stairs": 24,
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+ "construction-tunnel": 23,
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+ "construction-wall": 20,
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+ "flat-crosswalk": 3,
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+ "flat-curb": 7,
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+ "flat-cyclinglane": 4,
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+ "flat-parkingdriveway": 5,
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+ "flat-railtrack": 6,
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+ "flat-road": 1,
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+ "flat-sidewalk": 2,
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+ "human-person": 8,
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+ "human-rider": 9,
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+ "nature-terrain": 29,
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+ "nature-vegetation": 28,
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+ "object-pole": 25,
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+ "object-trafficlight": 27,
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+ "object-trafficsign": 26,
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+ "sky": 30,
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+ "unlabeled": 0,
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+ "vehicle-bicycle": 15,
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+ "vehicle-bus": 12,
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+ "vehicle-car": 10,
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+ "vehicle-caravan": 16,
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+ "vehicle-cartrailer": 17,
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+ "vehicle-motorcycle": 14,
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+ "vehicle-tramtrain": 13,
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+ "vehicle-truck": 11,
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+ "void-dynamic": 32,
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+ "void-ground": 31,
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+ "void-static": 33,
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+ "void-unclear": 34
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "mlp_ratios": [
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+ 4,
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+ 4,
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+ 4,
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+ 4
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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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+ 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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+ 2,
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+ 1
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+ ],
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+ "strides": [
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+ 4,
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+ 2,
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+ 2,
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+ 2
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.1"
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+ }
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