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saad7489
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segformer-b0-finetuned-segments-SixrayKnife8-19-2024

Image Segmentation
TensorBoard
Safetensors
segformer
vision
Generated from Trainer
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saad7489 commited on
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End of training

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Files changed (5) hide show
  1. README.md +20 -20
  2. config.json +6 -6
  3. model.safetensors +1 -1
  4. runs/Aug20_08-01-45_ab49fae2aabc/events.out.tfevents.1724140922.ab49fae2aabc.366.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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- base_model: nvidia/mit-b0
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  license: other
 
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  tags:
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  - vision
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  - image-segmentation
@@ -17,16 +17,16 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixraygunTest dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7816
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- - Mean Iou: 0.4625
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- - Mean Accuracy: 0.8009
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- - Overall Accuracy: 0.8059
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- - Accuracy No-label: nan
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- - Accuracy Object1: 0.6792
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- - Accuracy Object2: 0.9225
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- - Iou No-label: 0.0
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- - Iou Object1: 0.6389
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- - Iou Object2: 0.7485
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  ## Model description
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@@ -55,15 +55,15 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy No-label | Accuracy Object1 | Accuracy Object2 | Iou No-label | Iou Object1 | Iou Object2 |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------------:|:----------------:|:----------------:|:------------:|:-----------:|:-----------:|
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- | 0.9891 | 1.4286 | 20 | 1.0335 | 0.3298 | 0.6654 | 0.6772 | nan | 0.3809 | 0.9500 | 0.0 | 0.3618 | 0.6276 |
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- | 0.9534 | 2.8571 | 40 | 0.9094 | 0.3836 | 0.7262 | 0.7360 | nan | 0.4884 | 0.9640 | 0.0 | 0.4728 | 0.6778 |
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- | 0.8917 | 4.2857 | 60 | 0.8524 | 0.4227 | 0.7669 | 0.7743 | nan | 0.5876 | 0.9463 | 0.0 | 0.5603 | 0.7077 |
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- | 0.8488 | 5.7143 | 80 | 0.8163 | 0.4619 | 0.8056 | 0.8104 | nan | 0.6888 | 0.9223 | 0.0 | 0.6435 | 0.7422 |
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- | 0.8531 | 7.1429 | 100 | 0.7959 | 0.4541 | 0.7955 | 0.8008 | nan | 0.6679 | 0.9232 | 0.0 | 0.6264 | 0.7359 |
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- | 0.8254 | 8.5714 | 120 | 0.7843 | 0.4535 | 0.7927 | 0.7982 | nan | 0.6595 | 0.9259 | 0.0 | 0.6217 | 0.7389 |
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- | 0.832 | 10.0 | 140 | 0.7816 | 0.4625 | 0.8009 | 0.8059 | nan | 0.6792 | 0.9225 | 0.0 | 0.6389 | 0.7485 |
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  ### Framework versions
 
1
  ---
 
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  license: other
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+ base_model: nvidia/mit-b0
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  tags:
5
  - vision
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  - image-segmentation
 
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixraygunTest dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8400
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+ - Mean Iou: 0.5119
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+ - Mean Accuracy: 0.8558
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+ - Overall Accuracy: 0.8558
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+ - Accuracy Object1: nan
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+ - Accuracy Object2: 0.8556
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+ - Accuracy Object3: 0.8561
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+ - Iou Object1: 0.0
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+ - Iou Object2: 0.7670
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+ - Iou Object3: 0.7687
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Object1 | Accuracy Object2 | Accuracy Object3 | Iou Object1 | Iou Object2 | Iou Object3 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:----------------:|:----------------:|:-----------:|:-----------:|:-----------:|
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+ | 1.0078 | 1.4286 | 20 | 1.0664 | 0.3704 | 0.7172 | 0.7115 | nan | 0.6051 | 0.8292 | 0.0 | 0.5243 | 0.5870 |
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+ | 0.9646 | 2.8571 | 40 | 0.9611 | 0.4414 | 0.7944 | 0.7925 | nan | 0.7559 | 0.8330 | 0.0 | 0.6574 | 0.6668 |
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+ | 0.9287 | 4.2857 | 60 | 0.8994 | 0.4776 | 0.8308 | 0.8297 | nan | 0.8085 | 0.8532 | 0.0 | 0.7157 | 0.7172 |
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+ | 0.873 | 5.7143 | 80 | 0.8656 | 0.4944 | 0.8451 | 0.8440 | nan | 0.8231 | 0.8671 | 0.0 | 0.7390 | 0.7442 |
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+ | 0.8578 | 7.1429 | 100 | 0.8394 | 0.5069 | 0.8534 | 0.8532 | nan | 0.8493 | 0.8575 | 0.0 | 0.7602 | 0.7605 |
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+ | 0.8201 | 8.5714 | 120 | 0.8329 | 0.5102 | 0.8545 | 0.8546 | nan | 0.8558 | 0.8531 | 0.0 | 0.7648 | 0.7657 |
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+ | 0.8415 | 10.0 | 140 | 0.8400 | 0.5119 | 0.8558 | 0.8558 | nan | 0.8556 | 0.8561 | 0.0 | 0.7670 | 0.7687 |
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  ### Framework versions
config.json CHANGED
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  256
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  ],
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  "id2label": {
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- "0": "no-label",
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- "1": "object1",
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- "2": "object2"
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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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- "no-label": 0,
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- "object1": 1,
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- "object2": 2
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  },
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  "layer_norm_eps": 1e-06,
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  "mlp_ratios": [
 
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  256
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  ],
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  "id2label": {
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+ "0": "object1",
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+ "1": "object2",
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+ "2": "object3"
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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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+ "object1": 0,
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+ "object2": 1,
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+ "object3": 2
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  },
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  "layer_norm_eps": 1e-06,
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  "mlp_ratios": [
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