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slm-segformer-080823-b1
This model is a fine-tuned version of nvidia/mit-b1 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0257
- Validation Loss: 0.0271
- Validation Mean Iou: 0.8583
- Validation Mean Accuracy: 0.9196
- Validation Overall Accuracy: 0.9888
- Validation Per Category Iou: [0.98849374 0.72800628]
- Validation Per Category Accuracy: [0.99410982 0.84499592]
- Epoch: 9
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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Per Category Iou | Validation Per Category Accuracy | Epoch |
|---|---|---|---|---|---|---|---|
| 0.1099 | 0.0958 | 0.8134 | 0.9461 | 0.9824 | [0.98176563 0.64502586] | [0.98511039 0.90705184] | 0 |
| 0.0478 | 0.0523 | 0.8440 | 0.9449 | 0.9865 | [0.9860406 0.7019479] | [0.98964683 0.90022015] | 1 |
| 0.0379 | 0.0409 | 0.8476 | 0.9325 | 0.9873 | [0.98687303 0.70826431] | [0.99144882 0.87350047] | 2 |
| 0.0336 | 0.0331 | 0.8551 | 0.9394 | 0.9880 | [0.98757544 0.72269531] | [0.99166337 0.88706795] | 3 |
| 0.0310 | 0.0329 | 0.8541 | 0.9426 | 0.9878 | [0.98735586 0.72081351] | [0.99118853 0.89409615] | 4 |
| 0.0292 | 0.0317 | 0.8516 | 0.9348 | 0.9877 | [0.98729336 0.71599644] | [0.99171219 0.87789181] | 5 |
| 0.0282 | 0.0296 | 0.8572 | 0.9336 | 0.9884 | [0.98798391 0.72647977] | [0.99252058 0.87472321] | 6 |
| 0.0271 | 0.0319 | 0.8476 | 0.9253 | 0.9875 | [0.98709267 0.70802268] | [0.99221744 0.85835533] | 7 |
| 0.0267 | 0.0295 | 0.8549 | 0.9298 | 0.9882 | [0.98782022 0.72192985] | [0.9926388 0.86691624] | 8 |
| 0.0257 | 0.0271 | 0.8583 | 0.9196 | 0.9888 | [0.98849374 0.72800628] | [0.99410982 0.84499592] | 9 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Tokenizers 0.13.3
