|
--- |
|
license: other |
|
base_model: nvidia/mit-b5 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: Test-SegFormer_Mixed_Set2_788images_mit-b5_RGB |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Test-SegFormer_Mixed_Set2_788images_mit-b5_RGB |
|
|
|
This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1661 |
|
- Mean Iou: 0.7900 |
|
- Mean Accuracy: 0.8412 |
|
- Overall Accuracy: 0.9471 |
|
- Accuracy Background: 0.9799 |
|
- Accuracy Melt: 0.5677 |
|
- Accuracy Substrate: 0.9760 |
|
- Iou Background: 0.9430 |
|
- Iou Melt: 0.4987 |
|
- Iou Substrate: 0.9285 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 100 |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:| |
|
| 0.1897 | 0.7042 | 50 | 0.1661 | 0.7900 | 0.8412 | 0.9471 | 0.9799 | 0.5677 | 0.9760 | 0.9430 | 0.4987 | 0.9285 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
