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segformer-b0-finetuned-segments-greenhouse-oct-23

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +93 -0
  2. config.json +96 -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-segments-greenhouse-oct-23
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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-greenhouse-oct-23
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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 MexicanVanGogh/greenhouse dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7058
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+ - Mean Iou: 0.2227
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+ - Mean Accuracy: 0.2804
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+ - Overall Accuracy: 0.9101
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Object: nan
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+ - Accuracy Road: 0.9378
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+ - Accuracy Plant: 0.9667
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+ - Accuracy Iron: 0.0
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+ - Accuracy Wood: 0.0
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+ - Accuracy Wall: 0.1932
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+ - Accuracy Raw Road: nan
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+ - Accuracy Bottom Wall: 0.0
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+ - Accuracy Roof: 0.1457
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+ - Accuracy Grass: 0.0
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+ - Iou Unlabeled: nan
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+ - Iou Object: nan
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+ - Iou Road: 0.9039
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+ - Iou Plant: 0.8421
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+ - Iou Iron: 0.0
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+ - Iou Wood: 0.0
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+ - Iou Wall: 0.1521
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+ - Iou Raw Road: 0.0
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+ - Iou Bottom Wall: 0.0
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+ - Iou Roof: 0.1061
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+ - Iou Grass: 0.0
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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: 30
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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 Unlabeled | Accuracy Object | Accuracy Road | Accuracy Plant | Accuracy Iron | Accuracy Wood | Accuracy Wall | Accuracy Raw Road | Accuracy Bottom Wall | Accuracy Roof | Accuracy Grass | Iou Unlabeled | Iou Object | Iou Road | Iou Plant | Iou Iron | Iou Wood | Iou Wall | Iou Raw Road | Iou Bottom Wall | Iou Roof | Iou Grass |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:---------------:|:-------------:|:--------------:|:-------------:|:-------------:|:-------------:|:-----------------:|:--------------------:|:-------------:|:--------------:|:-------------:|:----------:|:--------:|:---------:|:--------:|:--------:|:--------:|:------------:|:---------------:|:--------:|:---------:|
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+ | 1.8756 | 2.86 | 20 | 2.0063 | 0.1415 | 0.2269 | 0.8216 | nan | nan | 0.7882 | 0.9674 | 0.0 | 0.0594 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7760 | 0.7552 | 0.0 | 0.0256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.3624 | 5.71 | 40 | 1.0910 | 0.1715 | 0.2380 | 0.8991 | nan | nan | 0.9206 | 0.9757 | 0.0 | 0.0077 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.8888 | 0.8220 | 0.0 | 0.0045 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4095 | 8.57 | 60 | 0.9033 | 0.1734 | 0.2392 | 0.9068 | nan | nan | 0.9264 | 0.9873 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.9000 | 0.8338 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.8802 | 11.43 | 80 | 0.7784 | 0.1764 | 0.2414 | 0.9165 | nan | nan | 0.9470 | 0.9823 | 0.0 | 0.0022 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.9155 | 0.8463 | 0.0 | 0.0021 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.0936 | 14.29 | 100 | 0.8060 | 0.1946 | 0.2405 | 0.9132 | nan | nan | 0.9400 | 0.9839 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.9100 | 0.8418 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.8086 | 17.14 | 120 | 0.7786 | 0.1940 | 0.2402 | 0.9115 | nan | nan | 0.9361 | 0.9852 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0006 | 0.0 | nan | nan | 0.9071 | 0.8380 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.0 |
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+ | 1.0669 | 20.0 | 140 | 0.7462 | 0.2072 | 0.2562 | 0.9088 | nan | nan | 0.9282 | 0.9853 | 0.0 | 0.0 | 0.0113 | nan | 0.0 | 0.1246 | 0.0 | nan | nan | 0.9010 | 0.8385 | 0.0 | 0.0 | 0.0102 | 0.0 | 0.0 | 0.1155 | 0.0 |
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+ | 0.7399 | 22.86 | 160 | 0.7328 | 0.2137 | 0.2662 | 0.9080 | nan | nan | 0.9290 | 0.9788 | 0.0 | 0.0 | 0.0814 | nan | 0.0 | 0.1405 | 0.0 | nan | nan | 0.8997 | 0.8389 | 0.0 | 0.0 | 0.0663 | 0.0 | 0.0 | 0.1181 | 0.0 |
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+ | 0.808 | 25.71 | 180 | 0.7296 | 0.2218 | 0.2797 | 0.9072 | nan | nan | 0.9277 | 0.9742 | 0.0 | 0.0 | 0.1840 | nan | 0.0 | 0.1515 | 0.0 | nan | nan | 0.8981 | 0.8404 | 0.0 | 0.0 | 0.1423 | 0.0 | 0.0 | 0.1155 | 0.0 |
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+ | 0.8494 | 28.57 | 200 | 0.7058 | 0.2227 | 0.2804 | 0.9101 | nan | nan | 0.9378 | 0.9667 | 0.0 | 0.0 | 0.1932 | nan | 0.0 | 0.1457 | 0.0 | nan | nan | 0.9039 | 0.8421 | 0.0 | 0.0 | 0.1521 | 0.0 | 0.0 | 0.1061 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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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+ "attention_probs_dropout_prob": 0.0,
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+ "classifier_dropout_prob": 0.1,
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+ "decoder_hidden_size": 256,
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+ "depths": [
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+ 2,
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+ 2,
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+ 2,
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+ 2
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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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+ 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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+ "0": "unlabeled",
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+ "1": "object",
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+ "2": "road",
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+ "3": "plant",
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+ "4": "iron",
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+ "5": "wood",
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+ "6": "wall",
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+ "7": "raw_road",
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+ "8": "bottom_wall",
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+ "9": "roof",
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+ "10": "grass"
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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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+ "bottom_wall": 8,
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+ "grass": 10,
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+ "iron": 4,
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+ "object": 1,
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+ "plant": 3,
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+ "raw_road": 7,
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+ "road": 2,
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+ "roof": 9,
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+ "unlabeled": 0,
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+ "wall": 6,
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+ "wood": 5
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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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+ ],
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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": "4.34.1"
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+ }
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