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--- |
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license: other |
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base_model: nvidia/mit-b2 |
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tags: |
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- image-segmentation |
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- vision |
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- generated_from_trainer |
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model-index: |
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- name: model1 |
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results: [] |
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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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# model1 |
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This model is a fine-tuned version of [nvidia/mit-b2](https://huggingface.co/nvidia/mit-b2) on the giuseppemartino/i-SAID_custom_or_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1646 |
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- Mean Iou: 0.2689 |
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- Mean Accuracy: 0.3089 |
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- Overall Accuracy: 0.3928 |
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- Accuracy Background: nan |
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- Accuracy Ship: 0.7889 |
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- Accuracy Small-vehicle: 0.3939 |
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- Accuracy Tennis-court: 0.6399 |
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- Accuracy Helicopter: nan |
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- Accuracy Basketball-court: 0.0 |
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- Accuracy Ground-track-field: 0.4337 |
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- Accuracy Swimming-pool: 0.6049 |
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- Accuracy Harbor: 0.3386 |
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- Accuracy Soccer-ball-field: 0.2551 |
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- Accuracy Plane: 0.0001 |
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- Accuracy Storage-tank: 0.0 |
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- Accuracy Baseball-diamond: 0.5217 |
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- Accuracy Large-vehicle: 0.3477 |
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- Accuracy Bridge: 0.0 |
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- Accuracy Roundabout: 0.0 |
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- Iou Background: 0.0 |
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- Iou Ship: 0.6137 |
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- Iou Small-vehicle: 0.3354 |
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- Iou Tennis-court: 0.6399 |
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- Iou Helicopter: nan |
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- Iou Basketball-court: 0.0 |
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- Iou Ground-track-field: 0.4084 |
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- Iou Swimming-pool: 0.6049 |
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- Iou Harbor: 0.3165 |
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- Iou Soccer-ball-field: 0.2514 |
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- Iou Plane: 0.0001 |
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- Iou Storage-tank: 0.0 |
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- Iou Baseball-diamond: 0.5217 |
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- Iou Large-vehicle: 0.3418 |
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- Iou Bridge: 0.0 |
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- Iou Roundabout: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- training_steps: 840 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Ship | Accuracy Small-vehicle | Accuracy Tennis-court | Accuracy Helicopter | Accuracy Basketball-court | Accuracy Ground-track-field | Accuracy Swimming-pool | Accuracy Harbor | Accuracy Soccer-ball-field | Accuracy Plane | Accuracy Storage-tank | Accuracy Baseball-diamond | Accuracy Large-vehicle | Accuracy Bridge | Accuracy Roundabout | Iou Background | Iou Ship | Iou Small-vehicle | Iou Tennis-court | Iou Helicopter | Iou Basketball-court | Iou Ground-track-field | Iou Swimming-pool | Iou Harbor | Iou Soccer-ball-field | Iou Plane | Iou Storage-tank | Iou Baseball-diamond | Iou Large-vehicle | Iou Bridge | Iou Roundabout | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:----------------------:|:---------------------:|:-------------------:|:-------------------------:|:---------------------------:|:----------------------:|:---------------:|:--------------------------:|:--------------:|:---------------------:|:-------------------------:|:----------------------:|:---------------:|:-------------------:|:--------------:|:--------:|:-----------------:|:----------------:|:--------------:|:--------------------:|:----------------------:|:-----------------:|:----------:|:---------------------:|:---------:|:----------------:|:--------------------:|:-----------------:|:----------:|:--------------:| |
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| 1.1466 | 1.0 | 105 | 0.3419 | 0.0260 | 0.0279 | 0.0687 | nan | 0.0068 | 0.0036 | 0.3562 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0240 | 0.0 | 0.0 | 0.0 | 0.0067 | 0.0036 | 0.3562 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0240 | 0.0 | 0.0 | |
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| 0.3289 | 2.0 | 210 | 0.2301 | 0.1252 | 0.1441 | 0.2674 | nan | 0.5316 | 0.1793 | 0.6775 | nan | 0.0 | 0.0324 | 0.1854 | 0.1185 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2923 | 0.0 | 0.0 | 0.0 | 0.4189 | 0.1612 | 0.6752 | nan | 0.0 | 0.0321 | 0.1854 | 0.1157 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2898 | 0.0 | 0.0 | |
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| 0.1819 | 3.0 | 315 | 0.1965 | 0.1611 | 0.1937 | 0.3286 | nan | 0.7305 | 0.2842 | 0.4229 | nan | 0.0 | 0.3566 | 0.2424 | 0.1707 | 0.0739 | 0.0 | 0.0 | 0.0 | 0.4300 | 0.0 | 0.0 | 0.0 | 0.5605 | 0.2492 | 0.4229 | nan | 0.0 | 0.2817 | 0.2424 | 0.1637 | 0.0738 | 0.0 | 0.0 | 0.0 | 0.4223 | 0.0 | 0.0 | |
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| 0.1505 | 4.0 | 420 | 0.1760 | 0.1987 | 0.2352 | 0.3689 | nan | 0.7552 | 0.3079 | 0.5796 | nan | 0.0 | 0.4515 | 0.4367 | 0.2065 | 0.1437 | 0.0 | 0.0 | 0.0 | 0.4115 | 0.0 | 0.0 | 0.0 | 0.5715 | 0.2762 | 0.5790 | nan | 0.0 | 0.3752 | 0.4367 | 0.1957 | 0.1435 | 0.0 | 0.0 | 0.0 | 0.4029 | 0.0 | 0.0 | |
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| 0.1269 | 5.0 | 525 | 0.1688 | 0.2239 | 0.2616 | 0.3561 | nan | 0.8249 | 0.3133 | 0.5309 | nan | 0.0 | 0.3966 | 0.6398 | 0.2513 | 0.1975 | 0.0003 | 0.0 | 0.1336 | 0.3738 | 0.0 | 0.0 | 0.0 | 0.6006 | 0.2833 | 0.5309 | nan | 0.0 | 0.3711 | 0.6398 | 0.2378 | 0.1957 | 0.0003 | 0.0 | 0.1336 | 0.3661 | 0.0 | 0.0 | |
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| 0.1012 | 6.0 | 630 | 0.1763 | 0.2563 | 0.3036 | 0.3830 | nan | 0.7977 | 0.4801 | 0.6774 | nan | 0.0 | 0.4913 | 0.7772 | 0.2993 | 0.2702 | 0.0 | 0.0 | 0.2024 | 0.2541 | 0.0 | 0.0 | 0.0 | 0.6060 | 0.3488 | 0.6774 | nan | 0.0 | 0.4359 | 0.7767 | 0.2816 | 0.2638 | 0.0 | 0.0 | 0.2024 | 0.2515 | 0.0 | 0.0 | |
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| 0.0996 | 7.0 | 735 | 0.1687 | 0.2515 | 0.2906 | 0.3644 | nan | 0.7947 | 0.3775 | 0.5884 | nan | 0.0 | 0.4452 | 0.5756 | 0.2734 | 0.2140 | 0.0 | 0.0 | 0.4769 | 0.3225 | 0.0 | 0.0 | 0.0 | 0.6093 | 0.3246 | 0.5884 | nan | 0.0 | 0.4081 | 0.5756 | 0.2599 | 0.2128 | 0.0 | 0.0 | 0.4769 | 0.3174 | 0.0 | 0.0 | |
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| 0.0945 | 8.0 | 840 | 0.1646 | 0.2689 | 0.3089 | 0.3928 | nan | 0.7889 | 0.3939 | 0.6399 | nan | 0.0 | 0.4337 | 0.6049 | 0.3386 | 0.2551 | 0.0001 | 0.0 | 0.5217 | 0.3477 | 0.0 | 0.0 | 0.0 | 0.6137 | 0.3354 | 0.6399 | nan | 0.0 | 0.4084 | 0.6049 | 0.3165 | 0.2514 | 0.0001 | 0.0 | 0.5217 | 0.3418 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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