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---
license: other
base_model: nvidia/mit-b0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-biofilm_MRCNNv1_train
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. -->
# segformer-finetuned-biofilm_MRCNNv1_train
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the heroza/biofilm_MRCNNv1_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Mean Iou: 0.5000
- Mean Accuracy: 1.0000
- Overall Accuracy: 1.0000
- Accuracy Background: 1.0000
- Accuracy Biofilm: nan
- Iou Background: 1.0000
- Iou Biofilm: 0.0
## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Biofilm | Iou Background | Iou Biofilm |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:----------------:|:--------------:|:-----------:|
| 0.262 | 1.0 | 136 | 0.0895 | 0.4984 | 0.9968 | 0.9968 | 0.9968 | nan | 0.9968 | 0.0 |
| 0.0826 | 2.0 | 272 | 0.0225 | 0.4995 | 0.9990 | 0.9990 | 0.9990 | nan | 0.9990 | 0.0 |
| 0.0225 | 3.0 | 408 | 0.0228 | 0.4985 | 0.9971 | 0.9971 | 0.9971 | nan | 0.9971 | 0.0 |
| 0.0141 | 4.0 | 544 | 0.0116 | 0.4997 | 0.9995 | 0.9995 | 0.9995 | nan | 0.9995 | 0.0 |
| 0.0093 | 5.0 | 680 | 0.0069 | 0.4996 | 0.9993 | 0.9993 | 0.9993 | nan | 0.9993 | 0.0 |
| 0.0054 | 6.0 | 816 | 0.0042 | 0.4999 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.004 | 7.0 | 952 | 0.0030 | 0.5000 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0034 | 8.0 | 1088 | 0.0027 | 0.4999 | 0.9998 | 0.9998 | 0.9998 | nan | 0.9998 | 0.0 |
| 0.0024 | 9.0 | 1224 | 0.0021 | 0.4999 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0021 | 10.0 | 1360 | 0.0015 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0017 | 11.0 | 1496 | 0.0019 | 0.4999 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0014 | 12.0 | 1632 | 0.0015 | 0.4999 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0012 | 13.0 | 1768 | 0.0010 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0009 | 14.0 | 1904 | 0.0010 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0008 | 15.0 | 2040 | 0.0009 | 0.5000 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0008 | 16.0 | 2176 | 0.0008 | 0.5000 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0006 | 17.0 | 2312 | 0.0009 | 0.4999 | 0.9999 | 0.9999 | 0.9999 | nan | 0.9999 | 0.0 |
| 0.0007 | 18.0 | 2448 | 0.0005 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0006 | 19.0 | 2584 | 0.0010 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0005 | 20.0 | 2720 | 0.0004 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0004 | 21.0 | 2856 | 0.0005 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0004 | 22.0 | 2992 | 0.0004 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0003 | 23.0 | 3128 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0004 | 24.0 | 3264 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0003 | 25.0 | 3400 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 26.0 | 3536 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0003 | 27.0 | 3672 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 28.0 | 3808 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 29.0 | 3944 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 30.0 | 4080 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 31.0 | 4216 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 32.0 | 4352 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0002 | 33.0 | 4488 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 34.0 | 4624 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 35.0 | 4760 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | nan | 1.0 | nan |
| 0.0002 | 36.0 | 4896 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 37.0 | 5032 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 38.0 | 5168 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 39.0 | 5304 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 40.0 | 5440 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 41.0 | 5576 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 42.0 | 5712 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 43.0 | 5848 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 44.0 | 5984 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 45.0 | 6120 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 46.0 | 6256 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 47.0 | 6392 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | nan | 1.0 | nan |
| 0.0001 | 48.0 | 6528 | 0.0000 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 49.0 | 6664 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 50.0 | 6800 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 51.0 | 6936 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 52.0 | 7072 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 53.0 | 7208 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 54.0 | 7344 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 55.0 | 7480 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 56.0 | 7616 | 0.0001 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 57.0 | 7752 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 58.0 | 7888 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 59.0 | 8024 | 0.0004 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 60.0 | 8160 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 61.0 | 8296 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 62.0 | 8432 | 0.0002 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 63.0 | 8568 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 64.0 | 8704 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | nan | 1.0 | nan |
| 0.0001 | 65.0 | 8840 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 66.0 | 8976 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 67.0 | 9112 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 68.0 | 9248 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 69.0 | 9384 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 70.0 | 9520 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 71.0 | 9656 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | nan | 1.0 | nan |
| 0.0001 | 72.0 | 9792 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 73.0 | 9928 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
| 0.0001 | 73.53 | 10000 | 0.0003 | 0.5000 | 1.0000 | 1.0000 | 1.0000 | nan | 1.0000 | 0.0 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.14.4
- Tokenizers 0.15.1
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