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# segformer-b0-finetuned-segments-ECHO-dev-05-v1

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the unreal-hug/REAL_DATASET_SEG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4592
- Mean Iou: 0.3826
- Mean Accuracy: 0.5892
- Overall Accuracy: 0.5467
- Accuracy Unlabeled: nan
- Accuracy Lv: 0.7143
- Accuracy Lr: 0.4323
- Accuracy Ra: 0.7629
- Accuracy La: 0.4472
- Iou Unlabeled: 0.0
- Iou Lv: 0.7065
- Iou Lr: 0.4317
- Iou Ra: 0.4223
- Iou La: 0.3527

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Lv | Accuracy Lr | Accuracy Ra | Accuracy La | Iou Unlabeled | Iou Lv | Iou Lr | Iou Ra | Iou La |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-------------:|:------:|:------:|:------:|:------:|
| 1.1252        | 2.86  | 20   | 1.3259          | 0.1971   | 0.3379        | 0.4375           | nan                | 0.0         | 0.6365      | 0.5291      | 0.1860      | 0.0           | 0.0    | 0.4923 | 0.3492 | 0.1439 |
| 0.9104        | 5.71  | 40   | 0.9589          | 0.1818   | 0.3421        | 0.3596           | nan                | 0.0145      | 0.3590      | 0.7644      | 0.2304      | 0.0           | 0.0144 | 0.3436 | 0.3778 | 0.1731 |
| 0.7567        | 8.57  | 60   | 0.7761          | 0.2203   | 0.3739        | 0.3852           | nan                | 0.0808      | 0.3882      | 0.6422      | 0.3844      | 0.0           | 0.0803 | 0.3778 | 0.4073 | 0.2360 |
| 0.7035        | 11.43 | 80   | 0.7442          | 0.2729   | 0.4718        | 0.4941           | nan                | 0.2145      | 0.5077      | 0.8370      | 0.3279      | 0.0           | 0.2134 | 0.4817 | 0.4073 | 0.2619 |
| 0.5781        | 14.29 | 100  | 0.6260          | 0.2876   | 0.4446        | 0.4279           | nan                | 0.4235      | 0.3777      | 0.5787      | 0.3986      | 0.0           | 0.3683 | 0.3761 | 0.4063 | 0.2873 |
| 0.5438        | 17.14 | 120  | 0.5559          | 0.3877   | 0.5412        | 0.5761           | nan                | 0.5803      | 0.6504      | 0.5190      | 0.4149      | 0.0           | 0.5671 | 0.6193 | 0.4171 | 0.3352 |
| 0.5198        | 20.0  | 140  | 0.5617          | 0.3724   | 0.5617        | 0.5335           | nan                | 0.6661      | 0.4532      | 0.7059      | 0.4216      | 0.0           | 0.6419 | 0.4532 | 0.4129 | 0.3540 |
| 0.4435        | 22.86 | 160  | 0.5393          | 0.4160   | 0.6198        | 0.6126           | nan                | 0.7555      | 0.5832      | 0.6962      | 0.4442      | 0.0           | 0.7000 | 0.5705 | 0.4873 | 0.3221 |
| 0.5002        | 25.71 | 180  | 0.5126          | 0.4094   | 0.6080        | 0.6043           | nan                | 0.6854      | 0.5833      | 0.6945      | 0.4687      | 0.0           | 0.6771 | 0.5761 | 0.4762 | 0.3176 |
| 0.4142        | 28.57 | 200  | 0.4874          | 0.3503   | 0.5361        | 0.4949           | nan                | 0.6967      | 0.3895      | 0.6436      | 0.4147      | 0.0           | 0.6287 | 0.3895 | 0.4106 | 0.3228 |
| 0.3092        | 31.43 | 220  | 0.4819          | 0.3857   | 0.6001        | 0.5534           | nan                | 0.7296      | 0.4267      | 0.8020      | 0.4423      | 0.0           | 0.7157 | 0.4267 | 0.4266 | 0.3595 |
| 0.2895        | 34.29 | 240  | 0.4969          | 0.3983   | 0.6220        | 0.5809           | nan                | 0.7353      | 0.4689      | 0.8050      | 0.4787      | 0.0           | 0.7265 | 0.4677 | 0.4474 | 0.3498 |
| 0.3046        | 37.14 | 260  | 0.4767          | 0.4248   | 0.6412        | 0.6115           | nan                | 0.7853      | 0.5270      | 0.7814      | 0.4711      | 0.0           | 0.7712 | 0.5199 | 0.4587 | 0.3742 |
| 0.3514        | 40.0  | 280  | 0.4531          | 0.3978   | 0.5989        | 0.5767           | nan                | 0.7112      | 0.5082      | 0.7478      | 0.4282      | 0.0           | 0.6979 | 0.5024 | 0.4353 | 0.3537 |
| 0.2891        | 42.86 | 300  | 0.4629          | 0.3842   | 0.5885        | 0.5488           | nan                | 0.7046      | 0.4397      | 0.7693      | 0.4403      | 0.0           | 0.6982 | 0.4366 | 0.4237 | 0.3623 |
| 0.2512        | 45.71 | 320  | 0.4584          | 0.3783   | 0.5794        | 0.5357           | nan                | 0.7144      | 0.4199      | 0.7390      | 0.4443      | 0.0           | 0.7016 | 0.4196 | 0.4134 | 0.3568 |
| 0.2695        | 48.57 | 340  | 0.4592          | 0.3826   | 0.5892        | 0.5467           | nan                | 0.7143      | 0.4323      | 0.7629      | 0.4472      | 0.0           | 0.7065 | 0.4317 | 0.4223 | 0.3527 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "other", "tags": ["vision", "image-segmentation", "generated_from_trainer"], "base_model": "nvidia/mit-b0", "model-index": [{"name": "segformer-b0-finetuned-segments-ECHO-dev-05-v1", "results": []}]}
transformers tensorboard safetensors segformer vision image-segmentation generated_from_trainer base_model:nvidia/mit-b0 license:other endpoints_compatible region:us