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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: foot-finetune-28-jan |
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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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# foot-finetune-28-jan |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the suncy13/FootImg dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1107 |
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- Mean Iou: 0.0 |
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- Mean Accuracy: nan |
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- Overall Accuracy: nan |
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- Accuracy Foot: nan |
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- Iou Foot: 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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Foot | Iou Foot | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------:|:--------:| |
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| 0.356 | 2.0 | 20 | 0.5295 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.2927 | 4.0 | 40 | 0.3244 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.2511 | 6.0 | 60 | 0.2386 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.2458 | 8.0 | 80 | 0.2305 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.2152 | 10.0 | 100 | 0.2065 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1996 | 12.0 | 120 | 0.1905 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1878 | 14.0 | 140 | 0.1823 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1902 | 16.0 | 160 | 0.1743 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1646 | 18.0 | 180 | 0.1572 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1512 | 20.0 | 200 | 0.1552 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1438 | 22.0 | 220 | 0.1415 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1355 | 24.0 | 240 | 0.1424 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1342 | 26.0 | 260 | 0.1322 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1355 | 28.0 | 280 | 0.1307 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1198 | 30.0 | 300 | 0.1238 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1179 | 32.0 | 320 | 0.1229 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1108 | 34.0 | 340 | 0.1196 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1145 | 36.0 | 360 | 0.1182 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1097 | 38.0 | 380 | 0.1168 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1199 | 40.0 | 400 | 0.1164 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1185 | 42.0 | 420 | 0.1138 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1026 | 44.0 | 440 | 0.1115 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1039 | 46.0 | 460 | 0.1100 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1091 | 48.0 | 480 | 0.1107 | 0.0 | nan | nan | nan | 0.0 | |
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| 0.1074 | 50.0 | 500 | 0.1107 | 0.0 | nan | nan | nan | 0.0 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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