metadata
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: custom-object-test3
results: []
custom-object-test3
This model is a fine-tuned version of nvidia/mit-b0 on the sungile/custom-object-masking3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6728
- Mean Iou: nan
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Unknown: nan
- Accuracy Background: nan
- Accuracy Object: nan
- Iou Unknown: nan
- Iou Background: nan
- Iou Object: nan
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unknown | Accuracy Background | Accuracy Object | Iou Unknown | Iou Background | Iou Object |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.4981 | 0.25 | 20 | 1.5526 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 1.2809 | 0.5 | 40 | 1.4961 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 1.025 | 0.75 | 60 | 1.3031 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 0.9376 | 1.0 | 80 | 0.9104 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 0.8413 | 1.25 | 100 | 0.8012 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 0.7648 | 1.5 | 120 | 0.7258 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 0.7118 | 1.75 | 140 | 0.7015 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 0.6699 | 2.0 | 160 | 0.6728 | nan | nan | nan | nan | nan | nan | nan | nan | nan |
Framework versions
- Transformers 4.47.1
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0