--- license: apache-2.0 base_model: facebook/hubert-base-ls960 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: hubert-classifier-aug-fold-2 results: [] --- # hubert-classifier-aug-fold-2 This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7842 - Accuracy: 0.8652 - Precision: 0.8801 - Recall: 0.8652 - F1: 0.8644 - Binary: 0.9058 ## 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: 0.0001 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| | No log | 0.24 | 50 | 4.4178 | 0.0232 | 0.0049 | 0.0232 | 0.0073 | 0.1830 | | No log | 0.48 | 100 | 4.3135 | 0.0787 | 0.0707 | 0.0787 | 0.0397 | 0.2956 | | No log | 0.72 | 150 | 3.9934 | 0.1124 | 0.0716 | 0.1124 | 0.0606 | 0.3658 | | No log | 0.96 | 200 | 3.6655 | 0.1506 | 0.1302 | 0.1506 | 0.0909 | 0.3913 | | 4.2392 | 1.2 | 250 | 3.3326 | 0.2262 | 0.1653 | 0.2262 | 0.1582 | 0.4506 | | 4.2392 | 1.44 | 300 | 2.9883 | 0.3401 | 0.2439 | 0.3401 | 0.2525 | 0.5362 | | 4.2392 | 1.68 | 350 | 2.6683 | 0.3700 | 0.3123 | 0.3700 | 0.2952 | 0.5566 | | 4.2392 | 1.92 | 400 | 2.4107 | 0.4052 | 0.3684 | 0.4052 | 0.3301 | 0.5785 | | 3.1531 | 2.16 | 450 | 2.0225 | 0.4966 | 0.4535 | 0.4966 | 0.4251 | 0.6475 | | 3.1531 | 2.4 | 500 | 1.7604 | 0.5618 | 0.5154 | 0.5618 | 0.4974 | 0.6929 | | 3.1531 | 2.63 | 550 | 1.5309 | 0.6090 | 0.6103 | 0.6090 | 0.5608 | 0.7267 | | 3.1531 | 2.87 | 600 | 1.3523 | 0.6599 | 0.6317 | 0.6599 | 0.6202 | 0.7609 | | 2.1046 | 3.11 | 650 | 1.2380 | 0.6742 | 0.6824 | 0.6742 | 0.6423 | 0.7706 | | 2.1046 | 3.35 | 700 | 1.1780 | 0.7004 | 0.7396 | 0.7004 | 0.6836 | 0.7886 | | 2.1046 | 3.59 | 750 | 0.9850 | 0.7483 | 0.7666 | 0.7483 | 0.7323 | 0.8229 | | 2.1046 | 3.83 | 800 | 0.9012 | 0.7715 | 0.7962 | 0.7715 | 0.7633 | 0.8399 | | 1.4918 | 4.07 | 850 | 0.8522 | 0.7700 | 0.7916 | 0.7700 | 0.7603 | 0.8387 | | 1.4918 | 4.31 | 900 | 0.7412 | 0.7948 | 0.8061 | 0.7948 | 0.7856 | 0.8564 | | 1.4918 | 4.55 | 950 | 0.7650 | 0.8015 | 0.8137 | 0.8015 | 0.7906 | 0.8622 | | 1.4918 | 4.79 | 1000 | 0.7356 | 0.8082 | 0.8232 | 0.8082 | 0.8019 | 0.8652 | | 1.1749 | 5.03 | 1050 | 0.6688 | 0.8097 | 0.8209 | 0.8097 | 0.8051 | 0.8678 | | 1.1749 | 5.27 | 1100 | 0.6470 | 0.8082 | 0.8308 | 0.8082 | 0.8040 | 0.8661 | | 1.1749 | 5.51 | 1150 | 0.6289 | 0.8262 | 0.8388 | 0.8262 | 0.8228 | 0.8781 | | 1.1749 | 5.75 | 1200 | 0.7243 | 0.8045 | 0.8206 | 0.8045 | 0.7992 | 0.8633 | | 1.1749 | 5.99 | 1250 | 0.5897 | 0.8367 | 0.8500 | 0.8367 | 0.8356 | 0.8870 | | 0.9784 | 6.23 | 1300 | 0.6412 | 0.8255 | 0.8397 | 0.8255 | 0.8249 | 0.8789 | | 0.9784 | 6.47 | 1350 | 0.5967 | 0.8367 | 0.8462 | 0.8367 | 0.8331 | 0.8860 | | 0.9784 | 6.71 | 1400 | 0.6342 | 0.8165 | 0.8356 | 0.8165 | 0.8142 | 0.8724 | | 0.9784 | 6.95 | 1450 | 0.6780 | 0.8232 | 0.8386 | 0.8232 | 0.8207 | 0.8776 | | 0.8541 | 7.19 | 1500 | 0.6008 | 0.8404 | 0.8532 | 0.8404 | 0.8382 | 0.8892 | | 0.8541 | 7.43 | 1550 | 0.5507 | 0.8524 | 0.8615 | 0.8524 | 0.8505 | 0.8964 | | 0.8541 | 7.66 | 1600 | 0.6125 | 0.8292 | 0.8435 | 0.8292 | 0.8267 | 0.8810 | | 0.8541 | 7.9 | 1650 | 0.5411 | 0.8577 | 0.8701 | 0.8577 | 0.8575 | 0.9013 | | 0.7624 | 8.14 | 1700 | 0.5236 | 0.8614 | 0.8693 | 0.8614 | 0.8603 | 0.9044 | | 0.7624 | 8.38 | 1750 | 0.5491 | 0.8472 | 0.8562 | 0.8472 | 0.8450 | 0.8948 | | 0.7624 | 8.62 | 1800 | 0.5398 | 0.8614 | 0.8686 | 0.8614 | 0.8583 | 0.9042 | | 0.7624 | 8.86 | 1850 | 0.5902 | 0.8509 | 0.8627 | 0.8509 | 0.8497 | 0.8969 | | 0.6922 | 9.1 | 1900 | 0.5808 | 0.8547 | 0.8686 | 0.8547 | 0.8543 | 0.8989 | | 0.6922 | 9.34 | 1950 | 0.6115 | 0.8390 | 0.8513 | 0.8390 | 0.8368 | 0.8886 | | 0.6922 | 9.58 | 2000 | 0.5479 | 0.8667 | 0.8759 | 0.8667 | 0.8645 | 0.9073 | | 0.6922 | 9.82 | 2050 | 0.6070 | 0.8487 | 0.8610 | 0.8487 | 0.8476 | 0.8953 | | 0.6251 | 10.06 | 2100 | 0.5700 | 0.8592 | 0.8724 | 0.8592 | 0.8589 | 0.9013 | | 0.6251 | 10.3 | 2150 | 0.5362 | 0.8742 | 0.8846 | 0.8742 | 0.8742 | 0.9122 | | 0.6251 | 10.54 | 2200 | 0.6288 | 0.8494 | 0.8669 | 0.8494 | 0.8499 | 0.8952 | | 0.6251 | 10.78 | 2250 | 0.5886 | 0.8569 | 0.8692 | 0.8569 | 0.8555 | 0.8995 | | 0.6044 | 11.02 | 2300 | 0.6453 | 0.8577 | 0.8712 | 0.8577 | 0.8556 | 0.9021 | | 0.6044 | 11.26 | 2350 | 0.6322 | 0.8479 | 0.8609 | 0.8479 | 0.8461 | 0.8950 | | 0.6044 | 11.5 | 2400 | 0.5856 | 0.8629 | 0.8713 | 0.8629 | 0.8619 | 0.9052 | | 0.6044 | 11.74 | 2450 | 0.5970 | 0.8569 | 0.8670 | 0.8569 | 0.8561 | 0.9013 | | 0.6044 | 11.98 | 2500 | 0.5703 | 0.8689 | 0.8789 | 0.8689 | 0.8676 | 0.9091 | | 0.5484 | 12.22 | 2550 | 0.6249 | 0.8629 | 0.8739 | 0.8629 | 0.8627 | 0.9043 | | 0.5484 | 12.46 | 2600 | 0.6848 | 0.8434 | 0.8565 | 0.8434 | 0.8404 | 0.8918 | | 0.5484 | 12.69 | 2650 | 0.5845 | 0.8659 | 0.8766 | 0.8659 | 0.8658 | 0.9072 | | 0.5484 | 12.93 | 2700 | 0.6151 | 0.8592 | 0.8695 | 0.8592 | 0.8579 | 0.9028 | | 0.5297 | 13.17 | 2750 | 0.5739 | 0.8734 | 0.8820 | 0.8734 | 0.8728 | 0.9122 | | 0.5297 | 13.41 | 2800 | 0.5720 | 0.8682 | 0.8797 | 0.8682 | 0.8671 | 0.9088 | | 0.5297 | 13.65 | 2850 | 0.5494 | 0.8779 | 0.8874 | 0.8779 | 0.8764 | 0.9158 | | 0.5297 | 13.89 | 2900 | 0.5730 | 0.8727 | 0.8813 | 0.8727 | 0.8719 | 0.9112 | | 0.5084 | 14.13 | 2950 | 0.6109 | 0.8652 | 0.8757 | 0.8652 | 0.8629 | 0.9073 | | 0.5084 | 14.37 | 3000 | 0.6417 | 0.8652 | 0.8762 | 0.8652 | 0.8642 | 0.9067 | | 0.5084 | 14.61 | 3050 | 0.5735 | 0.8712 | 0.8788 | 0.8712 | 0.8701 | 0.9101 | | 0.5084 | 14.85 | 3100 | 0.5614 | 0.8757 | 0.8835 | 0.8757 | 0.8743 | 0.9139 | | 0.4813 | 15.09 | 3150 | 0.6592 | 0.8644 | 0.8735 | 0.8644 | 0.8632 | 0.9064 | | 0.4813 | 15.33 | 3200 | 0.5960 | 0.8719 | 0.8786 | 0.8719 | 0.8702 | 0.9112 | | 0.4813 | 15.57 | 3250 | 0.5824 | 0.8742 | 0.8815 | 0.8742 | 0.8735 | 0.9127 | | 0.4813 | 15.81 | 3300 | 0.6188 | 0.8674 | 0.8767 | 0.8674 | 0.8668 | 0.9082 | | 0.4615 | 16.05 | 3350 | 0.5480 | 0.8749 | 0.8832 | 0.8749 | 0.8742 | 0.9131 | | 0.4615 | 16.29 | 3400 | 0.5980 | 0.8764 | 0.8844 | 0.8764 | 0.8760 | 0.9140 | | 0.4615 | 16.53 | 3450 | 0.5855 | 0.8742 | 0.8815 | 0.8742 | 0.8732 | 0.9120 | | 0.4615 | 16.77 | 3500 | 0.5869 | 0.8719 | 0.8832 | 0.8719 | 0.8717 | 0.9114 | | 0.4421 | 17.01 | 3550 | 0.6259 | 0.8674 | 0.8760 | 0.8674 | 0.8657 | 0.9077 | | 0.4421 | 17.25 | 3600 | 0.6427 | 0.8577 | 0.8684 | 0.8577 | 0.8569 | 0.9012 | | 0.4421 | 17.49 | 3650 | 0.6241 | 0.8749 | 0.8847 | 0.8749 | 0.8739 | 0.9133 | | 0.4421 | 17.72 | 3700 | 0.6669 | 0.8592 | 0.8688 | 0.8592 | 0.8574 | 0.9026 | | 0.4421 | 17.96 | 3750 | 0.5774 | 0.8757 | 0.8834 | 0.8757 | 0.8741 | 0.9140 | | 0.4298 | 18.2 | 3800 | 0.6578 | 0.8704 | 0.8766 | 0.8704 | 0.8681 | 0.9100 | | 0.4298 | 18.44 | 3850 | 0.6365 | 0.8712 | 0.8796 | 0.8712 | 0.8712 | 0.9088 | | 0.4298 | 18.68 | 3900 | 0.5537 | 0.8779 | 0.8845 | 0.8779 | 0.8759 | 0.9155 | | 0.4298 | 18.92 | 3950 | 0.6618 | 0.8757 | 0.8848 | 0.8757 | 0.8740 | 0.9129 | | 0.4154 | 19.16 | 4000 | 0.6952 | 0.8569 | 0.8681 | 0.8569 | 0.8555 | 0.9005 | | 0.4154 | 19.4 | 4050 | 0.6206 | 0.8727 | 0.8797 | 0.8727 | 0.8717 | 0.9116 | | 0.4154 | 19.64 | 4100 | 0.6469 | 0.8734 | 0.8846 | 0.8734 | 0.8726 | 0.9121 | | 0.4154 | 19.88 | 4150 | 0.6405 | 0.8674 | 0.8788 | 0.8674 | 0.8665 | 0.9081 | | 0.39 | 20.12 | 4200 | 0.6393 | 0.8809 | 0.8888 | 0.8809 | 0.8796 | 0.9176 | | 0.39 | 20.36 | 4250 | 0.6617 | 0.8779 | 0.8881 | 0.8779 | 0.8777 | 0.9145 | | 0.39 | 20.6 | 4300 | 0.6272 | 0.8697 | 0.8820 | 0.8697 | 0.8696 | 0.9098 | | 0.39 | 20.84 | 4350 | 0.6635 | 0.8704 | 0.8818 | 0.8704 | 0.8707 | 0.9098 | | 0.4019 | 21.08 | 4400 | 0.5965 | 0.8846 | 0.8943 | 0.8846 | 0.8849 | 0.9203 | | 0.4019 | 21.32 | 4450 | 0.6427 | 0.8764 | 0.8872 | 0.8764 | 0.8764 | 0.9145 | | 0.4019 | 21.56 | 4500 | 0.6726 | 0.8712 | 0.8799 | 0.8712 | 0.8699 | 0.9101 | | 0.4019 | 21.8 | 4550 | 0.5973 | 0.8772 | 0.8854 | 0.8772 | 0.8766 | 0.9159 | | 0.3718 | 22.04 | 4600 | 0.6342 | 0.8764 | 0.8868 | 0.8764 | 0.8759 | 0.9139 | | 0.3718 | 22.28 | 4650 | 0.6081 | 0.8846 | 0.8945 | 0.8846 | 0.8848 | 0.9193 | | 0.3718 | 22.51 | 4700 | 0.6140 | 0.8779 | 0.8900 | 0.8779 | 0.8767 | 0.9150 | | 0.3718 | 22.75 | 4750 | 0.6561 | 0.8719 | 0.8840 | 0.8719 | 0.8715 | 0.9116 | | 0.3718 | 22.99 | 4800 | 0.5921 | 0.8757 | 0.8853 | 0.8757 | 0.8746 | 0.9139 | | 0.3638 | 23.23 | 4850 | 0.6855 | 0.8719 | 0.8826 | 0.8719 | 0.8702 | 0.9106 | | 0.3638 | 23.47 | 4900 | 0.5923 | 0.8816 | 0.8933 | 0.8816 | 0.8813 | 0.9170 | | 0.3638 | 23.71 | 4950 | 0.6988 | 0.8629 | 0.8761 | 0.8629 | 0.8608 | 0.9049 | | 0.3638 | 23.95 | 5000 | 0.7042 | 0.8734 | 0.8840 | 0.8734 | 0.8730 | 0.9124 | | 0.3447 | 24.19 | 5050 | 0.7146 | 0.8667 | 0.8755 | 0.8667 | 0.8647 | 0.9071 | | 0.3447 | 24.43 | 5100 | 0.7134 | 0.8659 | 0.8754 | 0.8659 | 0.8647 | 0.9066 | | 0.3447 | 24.67 | 5150 | 0.6893 | 0.8682 | 0.8784 | 0.8682 | 0.8672 | 0.9083 | | 0.3447 | 24.91 | 5200 | 0.6617 | 0.8757 | 0.8887 | 0.8757 | 0.8750 | 0.9140 | | 0.3387 | 25.15 | 5250 | 0.6747 | 0.8652 | 0.8772 | 0.8652 | 0.8636 | 0.9050 | | 0.3387 | 25.39 | 5300 | 0.6693 | 0.8697 | 0.8794 | 0.8697 | 0.8684 | 0.9099 | | 0.3387 | 25.63 | 5350 | 0.7019 | 0.8727 | 0.8863 | 0.8727 | 0.8720 | 0.9121 | | 0.3387 | 25.87 | 5400 | 0.7221 | 0.8637 | 0.8793 | 0.8637 | 0.8626 | 0.9057 | | 0.3303 | 26.11 | 5450 | 0.6852 | 0.8734 | 0.8821 | 0.8734 | 0.8723 | 0.9130 | | 0.3303 | 26.35 | 5500 | 0.6092 | 0.8801 | 0.8883 | 0.8801 | 0.8796 | 0.9166 | | 0.3303 | 26.59 | 5550 | 0.6416 | 0.8801 | 0.8881 | 0.8801 | 0.8795 | 0.9170 | | 0.3303 | 26.83 | 5600 | 0.6762 | 0.8667 | 0.8763 | 0.8667 | 0.8646 | 0.9077 | | 0.3253 | 27.07 | 5650 | 0.6886 | 0.8742 | 0.8841 | 0.8742 | 0.8737 | 0.9121 | | 0.3253 | 27.31 | 5700 | 0.7574 | 0.8629 | 0.8742 | 0.8629 | 0.8602 | 0.9049 | | 0.3253 | 27.54 | 5750 | 0.6952 | 0.8749 | 0.8836 | 0.8749 | 0.8745 | 0.9143 | | 0.3253 | 27.78 | 5800 | 0.7068 | 0.8667 | 0.8786 | 0.8667 | 0.8663 | 0.9095 | | 0.3233 | 28.02 | 5850 | 0.6912 | 0.8749 | 0.8867 | 0.8749 | 0.8741 | 0.9141 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.3.0 - Datasets 2.19.1 - Tokenizers 0.15.1