--- license: other tags: - generated_from_keras_callback model-index: - name: AhamadShaik/SegFormer_PADDING_x.6 results: [] --- # AhamadShaik/SegFormer_PADDING_x.6 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: - Train Loss: 0.0159 - Train Dice Coef: 0.8034 - Train Iou: 0.6803 - Validation Loss: 0.0223 - Validation Dice Coef: 0.8606 - Validation Iou: 0.7573 - Train Lr: 1e-10 - Epoch: 99 ## 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': 1e-10, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Train Dice Coef | Train Iou | Validation Loss | Validation Dice Coef | Validation Iou | Train Lr | Epoch | |:----------:|:---------------:|:---------:|:---------------:|:--------------------:|:--------------:|:--------:|:-----:| | 0.2116 | 0.3018 | 0.1931 | 0.0863 | 0.6813 | 0.5211 | 1e-04 | 0 | | 0.0722 | 0.4966 | 0.3490 | 0.0565 | 0.7560 | 0.6108 | 1e-04 | 1 | | 0.0544 | 0.5768 | 0.4227 | 0.0465 | 0.7728 | 0.6368 | 1e-04 | 2 | | 0.0446 | 0.6305 | 0.4771 | 0.0379 | 0.8130 | 0.6869 | 1e-04 | 3 | | 0.0422 | 0.6479 | 0.4950 | 0.0366 | 0.8005 | 0.6719 | 1e-04 | 4 | | 0.0375 | 0.6776 | 0.5273 | 0.0315 | 0.8327 | 0.7155 | 1e-04 | 5 | | 0.0351 | 0.6926 | 0.5428 | 0.0311 | 0.8340 | 0.7177 | 1e-04 | 6 | | 0.0341 | 0.6967 | 0.5485 | 0.0295 | 0.8377 | 0.7228 | 1e-04 | 7 | | 0.0307 | 0.7246 | 0.5794 | 0.0278 | 0.8444 | 0.7328 | 1e-04 | 8 | | 0.0318 | 0.7119 | 0.5664 | 0.0278 | 0.8423 | 0.7297 | 1e-04 | 9 | | 0.0284 | 0.7362 | 0.5940 | 0.0280 | 0.8435 | 0.7314 | 1e-04 | 10 | | 0.0278 | 0.7382 | 0.5979 | 0.0284 | 0.8371 | 0.7232 | 1e-04 | 11 | | 0.0268 | 0.7429 | 0.6030 | 0.0261 | 0.8504 | 0.7419 | 1e-04 | 12 | | 0.0262 | 0.7464 | 0.6072 | 0.0285 | 0.8408 | 0.7280 | 1e-04 | 13 | | 0.0247 | 0.7560 | 0.6189 | 0.0255 | 0.8505 | 0.7419 | 1e-04 | 14 | | 0.0244 | 0.7580 | 0.6209 | 0.0249 | 0.8524 | 0.7450 | 1e-04 | 15 | | 0.0221 | 0.7719 | 0.6385 | 0.0246 | 0.8503 | 0.7422 | 1e-04 | 16 | | 0.0234 | 0.7623 | 0.6261 | 0.0233 | 0.8567 | 0.7516 | 1e-04 | 17 | | 0.0253 | 0.7527 | 0.6147 | 0.0258 | 0.8481 | 0.7401 | 1e-04 | 18 | | 0.0241 | 0.7597 | 0.6236 | 0.0258 | 0.8430 | 0.7331 | 1e-04 | 19 | | 0.0230 | 0.7657 | 0.6310 | 0.0224 | 0.8571 | 0.7522 | 1e-04 | 20 | | 0.0210 | 0.7755 | 0.6431 | 0.0220 | 0.8609 | 0.7577 | 1e-04 | 21 | | 0.0195 | 0.7867 | 0.6572 | 0.0231 | 0.8578 | 0.7531 | 1e-04 | 22 | | 0.0192 | 0.7880 | 0.6592 | 0.0226 | 0.8602 | 0.7568 | 1e-04 | 23 | | 0.0185 | 0.7909 | 0.6630 | 0.0231 | 0.8591 | 0.7549 | 1e-04 | 24 | | 0.0186 | 0.7906 | 0.6626 | 0.0221 | 0.8590 | 0.7551 | 1e-04 | 25 | | 0.0196 | 0.7836 | 0.6531 | 0.0239 | 0.8550 | 0.7491 | 1e-04 | 26 | | 0.0177 | 0.7975 | 0.6717 | 0.0223 | 0.8589 | 0.7549 | 5e-06 | 27 | | 0.0173 | 0.7979 | 0.6727 | 0.0228 | 0.8585 | 0.7542 | 5e-06 | 28 | | 0.0170 | 0.7980 | 0.6731 | 0.0215 | 0.8594 | 0.7556 | 5e-06 | 29 | | 0.0168 | 0.8003 | 0.6755 | 0.0213 | 0.8616 | 0.7590 | 5e-06 | 30 | | 0.0167 | 0.8016 | 0.6774 | 0.0211 | 0.8614 | 0.7587 | 5e-06 | 31 | | 0.0167 | 0.8044 | 0.6807 | 0.0217 | 0.8598 | 0.7562 | 5e-06 | 32 | | 0.0167 | 0.8048 | 0.6815 | 0.0211 | 0.8622 | 0.7599 | 5e-06 | 33 | | 0.0164 | 0.8013 | 0.6773 | 0.0213 | 0.8621 | 0.7596 | 5e-06 | 34 | | 0.0162 | 0.8025 | 0.6790 | 0.0216 | 0.8608 | 0.7578 | 5e-06 | 35 | | 0.0163 | 0.8018 | 0.6784 | 0.0212 | 0.8615 | 0.7587 | 5e-06 | 36 | | 0.0161 | 0.8043 | 0.6818 | 0.0211 | 0.8627 | 0.7605 | 2.5e-07 | 37 | | 0.0161 | 0.8025 | 0.6793 | 0.0218 | 0.8604 | 0.7572 | 2.5e-07 | 38 | | 0.0163 | 0.8039 | 0.6810 | 0.0211 | 0.8618 | 0.7592 | 2.5e-07 | 39 | | 0.0159 | 0.8044 | 0.6816 | 0.0215 | 0.8622 | 0.7597 | 2.5e-07 | 40 | | 0.0157 | 0.8068 | 0.6841 | 0.0213 | 0.8612 | 0.7584 | 2.5e-07 | 41 | | 0.0159 | 0.8063 | 0.6837 | 0.0214 | 0.8615 | 0.7588 | 1.25e-08 | 42 | | 0.0160 | 0.8040 | 0.6814 | 0.0217 | 0.8609 | 0.7578 | 1.25e-08 | 43 | | 0.0159 | 0.8072 | 0.6852 | 0.0213 | 0.8616 | 0.7589 | 1.25e-08 | 44 | | 0.0160 | 0.8062 | 0.6836 | 0.0215 | 0.8611 | 0.7581 | 1.25e-08 | 45 | | 0.0159 | 0.8045 | 0.6820 | 0.0211 | 0.8623 | 0.7600 | 1.25e-08 | 46 | | 0.0162 | 0.8027 | 0.6798 | 0.0210 | 0.8622 | 0.7599 | 6.25e-10 | 47 | | 0.0160 | 0.8039 | 0.6807 | 0.0218 | 0.8606 | 0.7575 | 6.25e-10 | 48 | | 0.0159 | 0.8093 | 0.6874 | 0.0220 | 0.8601 | 0.7566 | 6.25e-10 | 49 | | 0.0159 | 0.8072 | 0.6841 | 0.0217 | 0.8622 | 0.7596 | 6.25e-10 | 50 | | 0.0159 | 0.8045 | 0.6815 | 0.0213 | 0.8614 | 0.7586 | 6.25e-10 | 51 | | 0.0159 | 0.8111 | 0.6894 | 0.0216 | 0.8615 | 0.7588 | 6.25e-10 | 52 | | 0.0158 | 0.8066 | 0.6843 | 0.0213 | 0.8617 | 0.7592 | 1e-10 | 53 | | 0.0161 | 0.8042 | 0.6813 | 0.0212 | 0.8618 | 0.7592 | 1e-10 | 54 | | 0.0163 | 0.8058 | 0.6829 | 0.0221 | 0.8604 | 0.7570 | 1e-10 | 55 | | 0.0164 | 0.8017 | 0.6785 | 0.0214 | 0.8612 | 0.7583 | 1e-10 | 56 | | 0.0160 | 0.8059 | 0.6827 | 0.0210 | 0.8620 | 0.7595 | 1e-10 | 57 | | 0.0162 | 0.8038 | 0.6805 | 0.0216 | 0.8616 | 0.7587 | 1e-10 | 58 | | 0.0160 | 0.8022 | 0.6791 | 0.0222 | 0.8598 | 0.7562 | 1e-10 | 59 | | 0.0161 | 0.8045 | 0.6812 | 0.0215 | 0.8614 | 0.7585 | 1e-10 | 60 | | 0.0159 | 0.8026 | 0.6794 | 0.0213 | 0.8605 | 0.7572 | 1e-10 | 61 | | 0.0161 | 0.8069 | 0.6846 | 0.0216 | 0.8608 | 0.7577 | 1e-10 | 62 | | 0.0159 | 0.8088 | 0.6873 | 0.0209 | 0.8628 | 0.7607 | 1e-10 | 63 | | 0.0161 | 0.8016 | 0.6783 | 0.0212 | 0.8616 | 0.7588 | 1e-10 | 64 | | 0.0161 | 0.8031 | 0.6798 | 0.0213 | 0.8612 | 0.7583 | 1e-10 | 65 | | 0.0161 | 0.8038 | 0.6811 | 0.0215 | 0.8601 | 0.7566 | 1e-10 | 66 | | 0.0160 | 0.8052 | 0.6827 | 0.0216 | 0.8608 | 0.7576 | 1e-10 | 67 | | 0.0161 | 0.8051 | 0.6825 | 0.0216 | 0.8610 | 0.7580 | 1e-10 | 68 | | 0.0159 | 0.8055 | 0.6826 | 0.0218 | 0.8601 | 0.7568 | 1e-10 | 69 | | 0.0159 | 0.8024 | 0.6793 | 0.0212 | 0.8617 | 0.7591 | 1e-10 | 70 | | 0.0158 | 0.8043 | 0.6813 | 0.0214 | 0.8608 | 0.7578 | 1e-10 | 71 | | 0.0161 | 0.8074 | 0.6850 | 0.0212 | 0.8610 | 0.7579 | 1e-10 | 72 | | 0.0161 | 0.8066 | 0.6841 | 0.0216 | 0.8615 | 0.7586 | 1e-10 | 73 | | 0.0159 | 0.8065 | 0.6841 | 0.0214 | 0.8611 | 0.7582 | 1e-10 | 74 | | 0.0162 | 0.8039 | 0.6808 | 0.0212 | 0.8617 | 0.7591 | 1e-10 | 75 | | 0.0160 | 0.8036 | 0.6801 | 0.0214 | 0.8616 | 0.7589 | 1e-10 | 76 | | 0.0161 | 0.8100 | 0.6879 | 0.0211 | 0.8619 | 0.7595 | 1e-10 | 77 | | 0.0161 | 0.8049 | 0.6816 | 0.0211 | 0.8616 | 0.7590 | 1e-10 | 78 | | 0.0161 | 0.8037 | 0.6805 | 0.0221 | 0.8596 | 0.7558 | 1e-10 | 79 | | 0.0159 | 0.8044 | 0.6816 | 0.0219 | 0.8615 | 0.7587 | 1e-10 | 80 | | 0.0161 | 0.8031 | 0.6796 | 0.0214 | 0.8611 | 0.7581 | 1e-10 | 81 | | 0.0160 | 0.8016 | 0.6782 | 0.0209 | 0.8622 | 0.7599 | 1e-10 | 82 | | 0.0162 | 0.8040 | 0.6810 | 0.0211 | 0.8623 | 0.7601 | 1e-10 | 83 | | 0.0159 | 0.8065 | 0.6844 | 0.0210 | 0.8624 | 0.7602 | 1e-10 | 84 | | 0.0159 | 0.8064 | 0.6841 | 0.0216 | 0.8613 | 0.7585 | 1e-10 | 85 | | 0.0159 | 0.8068 | 0.6851 | 0.0212 | 0.8626 | 0.7604 | 1e-10 | 86 | | 0.0158 | 0.8049 | 0.6822 | 0.0222 | 0.8600 | 0.7564 | 1e-10 | 87 | | 0.0161 | 0.8028 | 0.6797 | 0.0210 | 0.8621 | 0.7597 | 1e-10 | 88 | | 0.0163 | 0.8050 | 0.6814 | 0.0218 | 0.8602 | 0.7567 | 1e-10 | 89 | | 0.0159 | 0.8077 | 0.6858 | 0.0215 | 0.8611 | 0.7582 | 1e-10 | 90 | | 0.0159 | 0.8067 | 0.6841 | 0.0213 | 0.8623 | 0.7599 | 1e-10 | 91 | | 0.0160 | 0.8064 | 0.6837 | 0.0213 | 0.8615 | 0.7588 | 1e-10 | 92 | | 0.0160 | 0.8073 | 0.6847 | 0.0209 | 0.8627 | 0.7606 | 1e-10 | 93 | | 0.0159 | 0.8056 | 0.6833 | 0.0214 | 0.8612 | 0.7583 | 1e-10 | 94 | | 0.0159 | 0.8073 | 0.6852 | 0.0213 | 0.8616 | 0.7590 | 1e-10 | 95 | | 0.0158 | 0.8051 | 0.6832 | 0.0219 | 0.8615 | 0.7587 | 1e-10 | 96 | | 0.0161 | 0.8053 | 0.6826 | 0.0220 | 0.8593 | 0.7555 | 1e-10 | 97 | | 0.0161 | 0.8059 | 0.6832 | 0.0218 | 0.8608 | 0.7577 | 1e-10 | 98 | | 0.0159 | 0.8034 | 0.6803 | 0.0223 | 0.8606 | 0.7573 | 1e-10 | 99 | ### Framework versions - Transformers 4.27.4 - TensorFlow 2.11.0 - Tokenizers 0.13.2