transformers pytorch segformer generated_from_trainer base_model:nvidia/mit-b0 license:other endpoints_compatible region:us
---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_trainer
model-index:
- name: segformer-b0_DsMetalDam_Augmented_Cropped
  results: []
---

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# segformer-b0_DsMetalDam_Augmented_Cropped

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2486
- Mean Iou: 0.6867
- Mean Accuracy: 0.7623
- Overall Accuracy: 0.9106
- Accuracy Matrix: 0.8910
- Accuracy Austenite: 0.9442
- Accuracy Martensite/austenite: 0.8061
- Accuracy Precipitate: 0.2109
- Accuracy Defect: 0.9591
- Iou Matrix: 0.8022
- Iou Austenite: 0.8886
- Iou Martensite/austenite: 0.6946
- Iou Precipitate: 0.1697
- Iou Defect: 0.8786

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Matrix | Accuracy Austenite | Accuracy Martensite/austenite | Accuracy Precipitate | Accuracy Defect | Iou Matrix | Iou Austenite | Iou Martensite/austenite | Iou Precipitate | Iou Defect |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------:|:------------------:|:-----------------------------:|:--------------------:|:---------------:|:----------:|:-------------:|:------------------------:|:---------------:|:----------:|
| 0.2546        | 1.0   | 343   | 0.3220          | 0.5965   | 0.6868        | 0.8757           | 0.8517          | 0.9218             | 0.7201                        | 0.0                  | 0.9404          | 0.7384     | 0.8585        | 0.5502                   | 0.0             | 0.8353     |
| 0.336         | 2.0   | 686   | 0.3159          | 0.5992   | 0.6766        | 0.8807           | 0.8816          | 0.9295             | 0.6220                        | 0.0                  | 0.9497          | 0.7474     | 0.8627        | 0.5429                   | 0.0             | 0.8428     |
| 0.2976        | 3.0   | 1029  | 0.3087          | 0.6057   | 0.6971        | 0.8807           | 0.8383          | 0.9325             | 0.7561                        | 0.0000               | 0.9583          | 0.7412     | 0.8629        | 0.5833                   | 0.0000          | 0.8411     |
| 0.2791        | 4.0   | 1372  | 0.2907          | 0.6175   | 0.6995        | 0.8886           | 0.8717          | 0.9290             | 0.7401                        | 0.0016               | 0.9548          | 0.7608     | 0.8674        | 0.6070                   | 0.0016          | 0.8507     |
| 0.2795        | 5.0   | 1715  | 0.2883          | 0.6264   | 0.7025        | 0.8906           | 0.8675          | 0.9369             | 0.7303                        | 0.0291               | 0.9489          | 0.7630     | 0.8689        | 0.6135                   | 0.0283          | 0.8584     |
| 0.2215        | 6.0   | 2058  | 0.2845          | 0.6316   | 0.7081        | 0.8924           | 0.8873          | 0.9252             | 0.7457                        | 0.0452               | 0.9373          | 0.7700     | 0.8700        | 0.6212                   | 0.0431          | 0.8536     |
| 0.2372        | 7.0   | 2401  | 0.2770          | 0.6343   | 0.7197        | 0.8931           | 0.8565          | 0.9373             | 0.7906                        | 0.0492               | 0.9651          | 0.7657     | 0.8715        | 0.6365                   | 0.0472          | 0.8504     |
| 0.3055        | 8.0   | 2744  | 0.2742          | 0.6337   | 0.7201        | 0.8950           | 0.8835          | 0.9220             | 0.8026                        | 0.0324               | 0.9603          | 0.7742     | 0.8728        | 0.6413                   | 0.0317          | 0.8482     |
| 0.2047        | 9.0   | 3087  | 0.2680          | 0.6497   | 0.7251        | 0.8982           | 0.8733          | 0.9384             | 0.7786                        | 0.0884               | 0.9468          | 0.7765     | 0.8766        | 0.6500                   | 0.0819          | 0.8634     |
| 0.1705        | 10.0  | 3430  | 0.2675          | 0.6489   | 0.7328        | 0.8987           | 0.8744          | 0.9336             | 0.8043                        | 0.0862               | 0.9654          | 0.7793     | 0.8767        | 0.6531                   | 0.0802          | 0.8550     |
| 0.2029        | 11.0  | 3773  | 0.2685          | 0.6523   | 0.7267        | 0.9003           | 0.8751          | 0.9443             | 0.7596                        | 0.0958               | 0.9589          | 0.7812     | 0.8779        | 0.6536                   | 0.0890          | 0.8600     |
| 0.1707        | 12.0  | 4116  | 0.2612          | 0.6591   | 0.7360        | 0.9015           | 0.8866          | 0.9324             | 0.7982                        | 0.1097               | 0.9532          | 0.7853     | 0.8788        | 0.6639                   | 0.0995          | 0.8679     |
| 0.2742        | 13.0  | 4459  | 0.2628          | 0.6512   | 0.7247        | 0.9022           | 0.8756          | 0.9442             | 0.7781                        | 0.0666               | 0.9593          | 0.7847     | 0.8797        | 0.6635                   | 0.0633          | 0.8651     |
| 0.2991        | 14.0  | 4802  | 0.2702          | 0.6653   | 0.7404        | 0.9025           | 0.8909          | 0.9368             | 0.7673                        | 0.1492               | 0.9578          | 0.7870     | 0.8799        | 0.6627                   | 0.1247          | 0.8722     |
| 0.229         | 15.0  | 5145  | 0.2599          | 0.6615   | 0.7395        | 0.9026           | 0.8723          | 0.9463             | 0.7800                        | 0.1303               | 0.9687          | 0.7850     | 0.8798        | 0.6682                   | 0.1143          | 0.8604     |
| 0.2004        | 16.0  | 5488  | 0.2595          | 0.6719   | 0.7473        | 0.9042           | 0.8854          | 0.9398             | 0.7863                        | 0.1735               | 0.9513          | 0.7898     | 0.8814        | 0.6719                   | 0.1442          | 0.8721     |
| 0.1944        | 17.0  | 5831  | 0.2564          | 0.6729   | 0.7486        | 0.9058           | 0.8940          | 0.9368             | 0.7895                        | 0.1693               | 0.9536          | 0.7936     | 0.8830        | 0.6778                   | 0.1418          | 0.8685     |
| 0.2068        | 18.0  | 6174  | 0.2539          | 0.6664   | 0.7450        | 0.9061           | 0.8915          | 0.9362             | 0.8051                        | 0.1245               | 0.9677          | 0.7940     | 0.8839        | 0.6801                   | 0.1102          | 0.8641     |
| 0.2461        | 19.0  | 6517  | 0.2494          | 0.6776   | 0.7603        | 0.9063           | 0.8756          | 0.9427             | 0.8251                        | 0.1941               | 0.9642          | 0.7927     | 0.8854        | 0.6800                   | 0.1585          | 0.8712     |
| 0.2252        | 20.0  | 6860  | 0.2498          | 0.6733   | 0.7461        | 0.9074           | 0.8813          | 0.9452             | 0.8043                        | 0.1456               | 0.9542          | 0.7947     | 0.8856        | 0.6843                   | 0.1284          | 0.8736     |
| 0.1975        | 21.0  | 7203  | 0.2519          | 0.6761   | 0.7516        | 0.9084           | 0.8960          | 0.9386             | 0.7992                        | 0.1656               | 0.9585          | 0.7989     | 0.8861        | 0.6862                   | 0.1412          | 0.8679     |
| 0.2356        | 22.0  | 7546  | 0.2506          | 0.6801   | 0.7526        | 0.9087           | 0.8956          | 0.9396             | 0.7972                        | 0.1764               | 0.9542          | 0.7991     | 0.8858        | 0.6890                   | 0.1486          | 0.8779     |
| 0.1838        | 23.0  | 7889  | 0.2510          | 0.6805   | 0.7554        | 0.9088           | 0.8835          | 0.9455             | 0.8068                        | 0.1824               | 0.9589          | 0.7978     | 0.8867        | 0.6892                   | 0.1516          | 0.8773     |
| 0.1576        | 24.0  | 8232  | 0.2511          | 0.6850   | 0.7658        | 0.9091           | 0.8913          | 0.9418             | 0.8021                        | 0.2291               | 0.9650          | 0.7996     | 0.8868        | 0.6891                   | 0.1765          | 0.8731     |
| 0.1504        | 25.0  | 8575  | 0.2505          | 0.6819   | 0.7590        | 0.9092           | 0.8869          | 0.9439             | 0.8077                        | 0.1916               | 0.9650          | 0.7992     | 0.8873        | 0.6890                   | 0.1587          | 0.8751     |
| 0.2196        | 26.0  | 8918  | 0.2530          | 0.6830   | 0.7597        | 0.9095           | 0.8946          | 0.9405             | 0.8035                        | 0.1985               | 0.9612          | 0.8010     | 0.8872        | 0.6900                   | 0.1610          | 0.8756     |
| 0.1781        | 27.0  | 9261  | 0.2509          | 0.6841   | 0.7596        | 0.9101           | 0.8901          | 0.9451             | 0.7993                        | 0.2000               | 0.9635          | 0.8010     | 0.8880        | 0.6930                   | 0.1635          | 0.8749     |
| 0.1578        | 28.0  | 9604  | 0.2485          | 0.6831   | 0.7591        | 0.9102           | 0.8874          | 0.9457             | 0.8064                        | 0.1912               | 0.9651          | 0.8008     | 0.8882        | 0.6942                   | 0.1585          | 0.8740     |
| 0.1931        | 29.0  | 9947  | 0.2495          | 0.6840   | 0.7579        | 0.9105           | 0.8893          | 0.9454             | 0.8042                        | 0.1899               | 0.9604          | 0.8016     | 0.8884        | 0.6940                   | 0.1580          | 0.8779     |
| 0.1582        | 30.0  | 10290 | 0.2486          | 0.6867   | 0.7623        | 0.9106           | 0.8910          | 0.9442             | 0.8061                        | 0.2109               | 0.9591          | 0.8022     | 0.8886        | 0.6946                   | 0.1697          | 0.8786     |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
