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# segformer-finetuned-4ss1st3r_s3gs3m_24Jan_negro-10k-steps

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the blzncz/4ss1st3r_s3gs3m_24Jan_negro dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2142
- Mean Iou: 0.5724
- Mean Accuracy: 0.7571
- Overall Accuracy: 0.9468
- Accuracy Bg: nan
- Accuracy Fallo cohesivo: 0.9826
- Accuracy Fallo malla: 0.7246
- Accuracy Fallo adhesivo: 0.9679
- Accuracy Fallo burbuja: 0.3533
- Iou Bg: 0.0
- Iou Fallo cohesivo: 0.9368
- Iou Fallo malla: 0.6678
- Iou Fallo adhesivo: 0.9310
- Iou Fallo burbuja: 0.3263

## 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 Bg | Accuracy Fallo cohesivo | Accuracy Fallo malla | Accuracy Fallo adhesivo | Accuracy Fallo burbuja | Iou Bg | Iou Fallo cohesivo | Iou Fallo malla | Iou Fallo adhesivo | Iou Fallo burbuja |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------:|:-----------------------:|:--------------------:|:-----------------------:|:----------------------:|:------:|:------------------:|:---------------:|:------------------:|:-----------------:|
| 0.1902        | 1.0   | 219   | 0.2615          | 0.5072   | 0.7247        | 0.9038           | nan         | 0.9203                  | 0.7991               | 0.9401                  | 0.2393                 | 0.0    | 0.8853             | 0.5556          | 0.9006             | 0.1944            |
| 0.1367        | 2.0   | 438   | 0.2067          | 0.5492   | 0.7602        | 0.9293           | nan         | 0.9599                  | 0.7487               | 0.9317                  | 0.4004                 | 0.0    | 0.9160             | 0.6120          | 0.8988             | 0.3195            |
| 0.1066        | 3.0   | 657   | 0.1963          | 0.5659   | 0.7814        | 0.9313           | nan         | 0.9520                  | 0.8022               | 0.9545                  | 0.4169                 | 0.0    | 0.9175             | 0.6270          | 0.9267             | 0.3584            |
| 0.1102        | 4.0   | 876   | 0.1595          | 0.5782   | 0.7756        | 0.9444           | nan         | 0.9727                  | 0.7669               | 0.9693                  | 0.3934                 | 0.0    | 0.9336             | 0.6828          | 0.9326             | 0.3422            |
| 0.1114        | 5.0   | 1095  | 0.1678          | 0.5772   | 0.7950        | 0.9378           | nan         | 0.9619                  | 0.7778               | 0.9756                  | 0.4648                 | 0.0    | 0.9255             | 0.6534          | 0.9151             | 0.3922            |
| 0.0897        | 6.0   | 1314  | 0.1726          | 0.5811   | 0.7976        | 0.9420           | nan         | 0.9701                  | 0.7598               | 0.9723                  | 0.4881                 | 0.0    | 0.9307             | 0.6613          | 0.9170             | 0.3965            |
| 0.0788        | 7.0   | 1533  | 0.2096          | 0.5491   | 0.7253        | 0.9342           | nan         | 0.9898                  | 0.5936               | 0.9381                  | 0.3797                 | 0.0    | 0.9235             | 0.5698          | 0.9149             | 0.3374            |
| 0.0788        | 8.0   | 1752  | 0.1574          | 0.5774   | 0.7733        | 0.9465           | nan         | 0.9726                  | 0.7858               | 0.9675                  | 0.3673                 | 0.0    | 0.9359             | 0.6914          | 0.9264             | 0.3331            |
| 0.0855        | 9.0   | 1971  | 0.1970          | 0.5406   | 0.7141        | 0.9380           | nan         | 0.9866                  | 0.6305               | 0.9708                  | 0.2687                 | 0.0    | 0.9274             | 0.5984          | 0.9224             | 0.2548            |
| 0.0761        | 10.0  | 2190  | 0.1903          | 0.5564   | 0.7479        | 0.9382           | nan         | 0.9746                  | 0.7050               | 0.9737                  | 0.3383                 | 0.0    | 0.9268             | 0.6272          | 0.9182             | 0.3098            |
| 0.0686        | 11.0  | 2409  | 0.1910          | 0.5562   | 0.7435        | 0.9393           | nan         | 0.9827                  | 0.6605               | 0.9738                  | 0.3572                 | 0.0    | 0.9285             | 0.6156          | 0.9209             | 0.3160            |
| 0.062         | 12.0  | 2628  | 0.2038          | 0.5453   | 0.7399        | 0.9334           | nan         | 0.9728                  | 0.6739               | 0.9811                  | 0.3317                 | 0.0    | 0.9214             | 0.6013          | 0.9035             | 0.3001            |
| 0.0586        | 13.0  | 2847  | 0.1914          | 0.5471   | 0.7342        | 0.9402           | nan         | 0.9758                  | 0.7103               | 0.9814                  | 0.2693                 | 0.0    | 0.9290             | 0.6397          | 0.9150             | 0.2517            |
| 0.0531        | 14.0  | 3066  | 0.1747          | 0.5716   | 0.7689        | 0.9449           | nan         | 0.9701                  | 0.7945               | 0.9588                  | 0.3522                 | 0.0    | 0.9339             | 0.6815          | 0.9280             | 0.3147            |
| 0.0522        | 15.0  | 3285  | 0.1933          | 0.5591   | 0.7399        | 0.9454           | nan         | 0.9810                  | 0.7222               | 0.9744                  | 0.2820                 | 0.0    | 0.9351             | 0.6603          | 0.9355             | 0.2645            |
| 0.059         | 16.0  | 3504  | 0.1897          | 0.5691   | 0.7878        | 0.9384           | nan         | 0.9499                  | 0.8594               | 0.9809                  | 0.3608                 | 0.0    | 0.9252             | 0.6741          | 0.9159             | 0.3303            |
| 0.0503        | 17.0  | 3723  | 0.1895          | 0.5652   | 0.7795        | 0.9365           | nan         | 0.9588                  | 0.7866               | 0.9808                  | 0.3917                 | 0.0    | 0.9238             | 0.6508          | 0.9004             | 0.3511            |
| 0.0518        | 18.0  | 3942  | 0.2131          | 0.5533   | 0.7332        | 0.9402           | nan         | 0.9807                  | 0.6877               | 0.9645                  | 0.2998                 | 0.0    | 0.9294             | 0.6248          | 0.9334             | 0.2790            |
| 0.0439        | 19.0  | 4161  | 0.2168          | 0.5565   | 0.7411        | 0.9388           | nan         | 0.9801                  | 0.6828               | 0.9567                  | 0.3448                 | 0.0    | 0.9278             | 0.6194          | 0.9234             | 0.3121            |
| 0.0459        | 20.0  | 4380  | 0.2688          | 0.5266   | 0.7127        | 0.9266           | nan         | 0.9824                  | 0.5567               | 0.9841                  | 0.3277                 | 0.0    | 0.9149             | 0.5329          | 0.8866             | 0.2987            |
| 0.043         | 21.0  | 4599  | 0.2395          | 0.5542   | 0.7409        | 0.9369           | nan         | 0.9821                  | 0.6444               | 0.9745                  | 0.3625                 | 0.0    | 0.9258             | 0.5974          | 0.9228             | 0.3248            |
| 0.0436        | 22.0  | 4818  | 0.1790          | 0.5736   | 0.7750        | 0.9441           | nan         | 0.9706                  | 0.7783               | 0.9694                  | 0.3819                 | 0.0    | 0.9331             | 0.6772          | 0.9143             | 0.3433            |
| 0.0443        | 23.0  | 5037  | 0.1843          | 0.5683   | 0.7613        | 0.9442           | nan         | 0.9756                  | 0.7470               | 0.9716                  | 0.3511                 | 0.0    | 0.9335             | 0.6684          | 0.9177             | 0.3219            |
| 0.0402        | 24.0  | 5256  | 0.2048          | 0.5666   | 0.7535        | 0.9429           | nan         | 0.9800                  | 0.7089               | 0.9706                  | 0.3544                 | 0.0    | 0.9324             | 0.6457          | 0.9302             | 0.3246            |
| 0.0399        | 25.0  | 5475  | 0.2102          | 0.5651   | 0.7524        | 0.9430           | nan         | 0.9830                  | 0.6875               | 0.9754                  | 0.3637                 | 0.0    | 0.9327             | 0.6412          | 0.9231             | 0.3287            |
| 0.0404        | 26.0  | 5694  | 0.1993          | 0.5792   | 0.7815        | 0.9460           | nan         | 0.9690                  | 0.8035               | 0.9697                  | 0.3837                 | 0.0    | 0.9351             | 0.6876          | 0.9289             | 0.3443            |
| 0.0388        | 27.0  | 5913  | 0.2024          | 0.5681   | 0.7501        | 0.9470           | nan         | 0.9821                  | 0.7343               | 0.9605                  | 0.3236                 | 0.0    | 0.9370             | 0.6715          | 0.9322             | 0.3001            |
| 0.0369        | 28.0  | 6132  | 0.1830          | 0.5701   | 0.7553        | 0.9481           | nan         | 0.9779                  | 0.7698               | 0.9608                  | 0.3126                 | 0.0    | 0.9379             | 0.6871          | 0.9323             | 0.2931            |
| 0.0373        | 29.0  | 6351  | 0.2162          | 0.5682   | 0.7535        | 0.9438           | nan         | 0.9828                  | 0.7011               | 0.9639                  | 0.3665                 | 0.0    | 0.9335             | 0.6482          | 0.9239             | 0.3352            |
| 0.0348        | 30.0  | 6570  | 0.2126          | 0.5640   | 0.7479        | 0.9435           | nan         | 0.9813                  | 0.7097               | 0.9623                  | 0.3384                 | 0.0    | 0.9330             | 0.6537          | 0.9197             | 0.3135            |
| 0.0354        | 31.0  | 6789  | 0.2025          | 0.5626   | 0.7467        | 0.9469           | nan         | 0.9795                  | 0.7453               | 0.9725                  | 0.2896                 | 0.0    | 0.9368             | 0.6762          | 0.9285             | 0.2716            |
| 0.0344        | 32.0  | 7008  | 0.1973          | 0.5786   | 0.7739        | 0.9469           | nan         | 0.9734                  | 0.7828               | 0.9698                  | 0.3695                 | 0.0    | 0.9364             | 0.6853          | 0.9326             | 0.3389            |
| 0.0333        | 33.0  | 7227  | 0.2199          | 0.5722   | 0.7624        | 0.9438           | nan         | 0.9817                  | 0.7045               | 0.9696                  | 0.3940                 | 0.0    | 0.9334             | 0.6481          | 0.9287             | 0.3510            |
| 0.0345        | 34.0  | 7446  | 0.2052          | 0.5791   | 0.7724        | 0.9465           | nan         | 0.9799                  | 0.7347               | 0.9736                  | 0.4015                 | 0.0    | 0.9363             | 0.6698          | 0.9311             | 0.3582            |
| 0.0326        | 35.0  | 7665  | 0.2176          | 0.5758   | 0.7629        | 0.9462           | nan         | 0.9835                  | 0.7124               | 0.9689                  | 0.3868                 | 0.0    | 0.9362             | 0.6595          | 0.9345             | 0.3490            |
| 0.034         | 36.0  | 7884  | 0.2247          | 0.5717   | 0.7557        | 0.9453           | nan         | 0.9841                  | 0.7033               | 0.9661                  | 0.3694                 | 0.0    | 0.9352             | 0.6533          | 0.9331             | 0.3369            |
| 0.0324        | 37.0  | 8103  | 0.1957          | 0.5797   | 0.7736        | 0.9490           | nan         | 0.9763                  | 0.7801               | 0.9725                  | 0.3657                 | 0.0    | 0.9390             | 0.6963          | 0.9299             | 0.3333            |
| 0.0332        | 38.0  | 8322  | 0.1996          | 0.5770   | 0.7644        | 0.9478           | nan         | 0.9826                  | 0.7310               | 0.9696                  | 0.3743                 | 0.0    | 0.9379             | 0.6741          | 0.9336             | 0.3393            |
| 0.0332        | 39.0  | 8541  | 0.2129          | 0.5638   | 0.7423        | 0.9449           | nan         | 0.9845                  | 0.7021               | 0.9616                  | 0.3212                 | 0.0    | 0.9348             | 0.6514          | 0.9328             | 0.3001            |
| 0.03          | 40.0  | 8760  | 0.2283          | 0.5694   | 0.7539        | 0.9441           | nan         | 0.9840                  | 0.6931               | 0.9686                  | 0.3699                 | 0.0    | 0.9339             | 0.6464          | 0.9277             | 0.3387            |
| 0.0319        | 41.0  | 8979  | 0.2013          | 0.5741   | 0.7624        | 0.9471           | nan         | 0.9804                  | 0.7416               | 0.9670                  | 0.3606                 | 0.0    | 0.9370             | 0.6760          | 0.9277             | 0.3300            |
| 0.0361        | 42.0  | 9198  | 0.2094          | 0.5709   | 0.7568        | 0.9463           | nan         | 0.9810                  | 0.7317               | 0.9663                  | 0.3483                 | 0.0    | 0.9362             | 0.6689          | 0.9279             | 0.3216            |
| 0.0304        | 43.0  | 9417  | 0.2098          | 0.5731   | 0.7586        | 0.9468           | nan         | 0.9821                  | 0.7282               | 0.9666                  | 0.3575                 | 0.0    | 0.9368             | 0.6700          | 0.9295             | 0.3293            |
| 0.0303        | 44.0  | 9636  | 0.2155          | 0.5705   | 0.7554        | 0.9470           | nan         | 0.9814                  | 0.7329               | 0.9702                  | 0.3370                 | 0.0    | 0.9369             | 0.6718          | 0.9301             | 0.3137            |
| 0.03          | 45.0  | 9855  | 0.2183          | 0.5703   | 0.7541        | 0.9464           | nan         | 0.9825                  | 0.7229               | 0.9677                  | 0.3435                 | 0.0    | 0.9364             | 0.6657          | 0.9311             | 0.3181            |
| 0.0301        | 45.66 | 10000 | 0.2142          | 0.5724   | 0.7571        | 0.9468           | nan         | 0.9826                  | 0.7246               | 0.9679                  | 0.3533                 | 0.0    | 0.9368             | 0.6678          | 0.9310             | 0.3263            |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cpu
- Datasets 2.13.1
- Tokenizers 0.13.3

{"license": "other", "tags": ["image-segmentation", "vision", "generated_from_trainer"], "model-index": [{"name": "segformer-finetuned-4ss1st3r_s3gs3m_24Jan_negro-10k-steps", "results": []}]}
transformers pytorch tensorboard segformer image-segmentation vision generated_from_trainer license:other endpoints_compatible region:us