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# segformer_rust

This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1438
- Mean Iou: 0.7943
- Mean Accuracy: 0.8621
- Overall Accuracy: 0.9463
- Per Category Iou: [0.9404316292856895, 0.6481512759943856]
- Per Category Accuracy: [0.9766097421311045, 0.7476136089750051]

## 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: 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 | Per Category Iou                         | Per Category Accuracy                    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:----------------------------------------:|
| 0.2683        | 1.0   | 514   | 0.1919          | 0.7319   | 0.8203        | 0.9254           | [0.9180806580950376, 0.5456807971830461] | [0.9632417779264837, 0.6772761097220785] |
| 0.2221        | 2.0   | 1028  | 0.1848          | 0.7247   | 0.7906        | 0.9285           | [0.9222502676042136, 0.5272319457425635] | [0.9780221080448669, 0.6032531950921799] |
| 0.2051        | 3.0   | 1542  | 0.1798          | 0.7523   | 0.8476        | 0.9301           | [0.9226057238240142, 0.5819673887381934] | [0.9598172268335441, 0.7353887410800054] |
| 0.1996        | 4.0   | 2056  | 0.1662          | 0.7530   | 0.8151        | 0.9366           | [0.9305887422755489, 0.5753549591140691] | [0.9802446445708194, 0.6499256145141094] |
| 0.1878        | 5.0   | 2570  | 0.1613          | 0.7695   | 0.8443        | 0.9386           | [0.9321977696827667, 0.6067612442121683] | [0.972541727740175, 0.7160658070940397]  |
| 0.1848        | 6.0   | 3084  | 0.1579          | 0.7659   | 0.8299        | 0.9395           | [0.9335431699668292, 0.5982432303010027] | [0.9789606327074537, 0.6808199676860336] |
| 0.1739        | 7.0   | 3598  | 0.1543          | 0.7799   | 0.8516        | 0.9419           | [0.9357233119518715, 0.6240100443072397] | [0.9744037993799354, 0.7287987165292924] |
| 0.1742        | 8.0   | 4112  | 0.1607          | 0.7737   | 0.8667        | 0.9369           | [0.9296752366973121, 0.6176824708083143] | [0.9620707480253384, 0.7713870499643393] |
| 0.1631        | 9.0   | 4626  | 0.1553          | 0.7803   | 0.8636        | 0.9402           | [0.9335684843016983, 0.626952054351963]  | [0.9678138198093251, 0.7593407854928076] |
| 0.1631        | 10.0  | 5140  | 0.1564          | 0.7679   | 0.8406        | 0.9386           | [0.9322118932460649, 0.6035637849191774] | [0.9738013828280326, 0.7073043940670594] |
| 0.1577        | 11.0  | 5654  | 0.1499          | 0.7836   | 0.8520        | 0.9434           | [0.9373956576514434, 0.6297874494960901] | [0.9763014923228973, 0.7277053858903674] |
| 0.1522        | 12.0  | 6168  | 0.1515          | 0.7781   | 0.8454        | 0.9422           | [0.9361248378060324, 0.6200926437502748] | [0.9769566337905029, 0.7138379976069665] |
| 0.1486        | 13.0  | 6682  | 0.1531          | 0.7766   | 0.8485        | 0.9410           | [0.9347900233191081, 0.618411826576312]  | [0.9743083731504567, 0.7226475641364578] |
| 0.146         | 14.0  | 7196  | 0.1568          | 0.7835   | 0.8667        | 0.9412           | [0.9345511743761084, 0.6325140238903502] | [0.9679584694275379, 0.7654769806378111] |
| 0.1453        | 15.0  | 7710  | 0.1485          | 0.7837   | 0.8473        | 0.9442           | [0.938357945982732, 0.6290898844632448]  | [0.9790292010707323, 0.7156414504087399] |
| 0.1439        | 16.0  | 8224  | 0.1492          | 0.7896   | 0.8623        | 0.9444           | [0.9382510027549076, 0.6409378390750833] | [0.973914066583286, 0.7506284726295933]  |
| 0.1385        | 17.0  | 8738  | 0.1494          | 0.7790   | 0.8369        | 0.9439           | [0.938230866841315, 0.6196920559815114]  | [0.9823649345853678, 0.6913889357135595] |
| 0.1375        | 18.0  | 9252  | 0.1515          | 0.7847   | 0.8549        | 0.9435           | [0.9373782356302373, 0.6321131725666339] | [0.975314658131637, 0.7344851844673589]  |
| 0.1353        | 19.0  | 9766  | 0.1450          | 0.7929   | 0.8610        | 0.9459           | [0.9399812074698386, 0.6457742806194801] | [0.9764190916833184, 0.7456795800307741] |
| 0.1317        | 20.0  | 10280 | 0.1453          | 0.7906   | 0.8584        | 0.9453           | [0.9394006951099269, 0.6417152113828789] | [0.9765905703089925, 0.7402706100619615] |
| 0.1292        | 21.0  | 10794 | 0.1565          | 0.7788   | 0.8416        | 0.9431           | [0.9372341895291594, 0.6204583221235739] | [0.9795794314033889, 0.7035825637871398] |
| 0.1284        | 22.0  | 11308 | 0.1487          | 0.7879   | 0.8532        | 0.9450           | [0.9391595949869292, 0.6366277680932542] | [0.9780565365202, 0.7282789363894756]    |
| 0.1279        | 23.0  | 11822 | 0.1461          | 0.7927   | 0.8629        | 0.9456           | [0.9395641382795358, 0.6458609695526066] | [0.9752807298744423, 0.7506032283294566] |
| 0.1262        | 24.0  | 12336 | 0.1436          | 0.7934   | 0.8633        | 0.9458           | [0.9398055111519206, 0.6469847970011983] | [0.9754426177792707, 0.7512221554580607] |
| 0.1223        | 25.0  | 12850 | 0.1465          | 0.7945   | 0.8622        | 0.9464           | [0.9404797675363489, 0.6484203969264617] | [0.9766238155760367, 0.7478641586538628] |
| 0.1234        | 26.0  | 13364 | 0.1435          | 0.7925   | 0.8570        | 0.9463           | [0.9405453729701521, 0.6444525239879496] | [0.9784625404961454, 0.735513574144182]  |
| 0.1223        | 27.0  | 13878 | 0.1464          | 0.7937   | 0.8618        | 0.9461           | [0.9402290147962161, 0.6472276210560935] | [0.976462283595653, 0.7471743581526247]  |
| 0.1196        | 28.0  | 14392 | 0.1450          | 0.7929   | 0.8589        | 0.9462           | [0.9403789254222912, 0.645380249186489]  | [0.9776359685007636, 0.7400721898628863] |
| 0.1199        | 29.0  | 14906 | 0.1451          | 0.7919   | 0.8563        | 0.9462           | [0.9403753807784087, 0.6433302809940281] | [0.9784796056303284, 0.7341607320998506] |
| 0.1208        | 30.0  | 15420 | 0.1438          | 0.7943   | 0.8621        | 0.9463           | [0.9404316292856895, 0.6481512759943856] | [0.9766097421311045, 0.7476136089750051] |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "other", "tags": ["generated_from_trainer"], "base_model": "nvidia/mit-b3", "model-index": [{"name": "segformer_rust", "results": []}]}
transformers pytorch segformer generated_from_trainer base_model:nvidia/mit-b3 license:other endpoints_compatible region:us