--- license: cc-by-nc-4.0 base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h tags: - generated_from_trainer metrics: - accuracy model-index: - name: viet_tones_model results: [] --- # viet_tones_model This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9783 - Accuracy: 0.5972 ## 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: 5e-05 - 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_ratio: 0.1 - num_epochs: 110 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.89 | 6 | 1.7955 | 0.1296 | | 1.7924 | 1.93 | 13 | 1.7938 | 0.1343 | | 1.7919 | 2.96 | 20 | 1.7916 | 0.2037 | | 1.7919 | 4.0 | 27 | 1.7907 | 0.1713 | | 1.7903 | 4.89 | 33 | 1.7886 | 0.1852 | | 1.7883 | 5.93 | 40 | 1.7798 | 0.2269 | | 1.7883 | 6.96 | 47 | 1.7487 | 0.25 | | 1.7717 | 8.0 | 54 | 1.7104 | 0.2407 | | 1.726 | 8.89 | 60 | 1.6488 | 0.2685 | | 1.726 | 9.93 | 67 | 1.5835 | 0.2731 | | 1.6651 | 10.96 | 74 | 1.6020 | 0.2778 | | 1.6332 | 12.0 | 81 | 1.5351 | 0.2778 | | 1.6332 | 12.89 | 87 | 1.4977 | 0.2963 | | 1.5708 | 13.93 | 94 | 1.4903 | 0.2870 | | 1.5543 | 14.96 | 101 | 1.4671 | 0.2731 | | 1.5543 | 16.0 | 108 | 1.3992 | 0.3194 | | 1.4872 | 16.89 | 114 | 1.3854 | 0.3009 | | 1.4861 | 17.93 | 121 | 1.3411 | 0.3426 | | 1.4861 | 18.96 | 128 | 1.3142 | 0.3472 | | 1.4281 | 20.0 | 135 | 1.3021 | 0.4259 | | 1.38 | 20.89 | 141 | 1.2657 | 0.4028 | | 1.38 | 21.93 | 148 | 1.2372 | 0.4352 | | 1.3472 | 22.96 | 155 | 1.2341 | 0.4815 | | 1.3029 | 24.0 | 162 | 1.1815 | 0.4306 | | 1.3029 | 24.89 | 168 | 1.1797 | 0.4954 | | 1.3042 | 25.93 | 175 | 1.1403 | 0.4583 | | 1.281 | 26.96 | 182 | 1.1349 | 0.4722 | | 1.281 | 28.0 | 189 | 1.1369 | 0.4907 | | 1.2614 | 28.89 | 195 | 1.0999 | 0.4954 | | 1.2133 | 29.93 | 202 | 1.1677 | 0.4676 | | 1.2133 | 30.96 | 209 | 1.0785 | 0.5 | | 1.2527 | 32.0 | 216 | 1.1092 | 0.4861 | | 1.1722 | 32.89 | 222 | 1.0424 | 0.5185 | | 1.1722 | 33.93 | 229 | 1.0791 | 0.4907 | | 1.1225 | 34.96 | 236 | 1.0447 | 0.4907 | | 1.1447 | 36.0 | 243 | 1.0777 | 0.4583 | | 1.1447 | 36.89 | 249 | 1.0141 | 0.4954 | | 1.1484 | 37.93 | 256 | 1.0196 | 0.5324 | | 1.11 | 38.96 | 263 | 0.9791 | 0.5417 | | 1.046 | 40.0 | 270 | 0.9798 | 0.5231 | | 1.046 | 40.89 | 276 | 0.9366 | 0.5694 | | 1.0582 | 41.93 | 283 | 0.9645 | 0.5602 | | 1.0569 | 42.96 | 290 | 0.9764 | 0.5694 | | 1.0569 | 44.0 | 297 | 1.0340 | 0.5324 | | 1.028 | 44.89 | 303 | 0.9969 | 0.5463 | | 1.04 | 45.93 | 310 | 1.0251 | 0.5185 | | 1.04 | 46.96 | 317 | 1.0447 | 0.5417 | | 0.9889 | 48.0 | 324 | 0.9487 | 0.5324 | | 1.0055 | 48.89 | 330 | 1.0147 | 0.5 | | 1.0055 | 49.93 | 337 | 1.0015 | 0.5046 | | 0.9955 | 50.96 | 344 | 0.9763 | 0.5278 | | 0.9382 | 52.0 | 351 | 1.0306 | 0.5278 | | 0.9382 | 52.89 | 357 | 0.9970 | 0.5463 | | 0.9601 | 53.93 | 364 | 0.9487 | 0.5741 | | 0.9736 | 54.96 | 371 | 0.9658 | 0.5463 | | 0.9736 | 56.0 | 378 | 0.9789 | 0.5602 | | 0.9237 | 56.89 | 384 | 0.9940 | 0.5463 | | 0.9588 | 57.93 | 391 | 0.9778 | 0.5463 | | 0.9588 | 58.96 | 398 | 0.9789 | 0.5648 | | 0.9393 | 60.0 | 405 | 0.9612 | 0.5602 | | 0.9291 | 60.89 | 411 | 0.9141 | 0.5556 | | 0.9291 | 61.93 | 418 | 0.9770 | 0.5463 | | 0.929 | 62.96 | 425 | 0.9385 | 0.5556 | | 0.9448 | 64.0 | 432 | 0.9504 | 0.5463 | | 0.9448 | 64.89 | 438 | 0.9984 | 0.5463 | | 0.9426 | 65.93 | 445 | 0.9228 | 0.5602 | | 0.8949 | 66.96 | 452 | 0.9729 | 0.5509 | | 0.8949 | 68.0 | 459 | 0.9825 | 0.5602 | | 0.9041 | 68.89 | 465 | 0.9769 | 0.5509 | | 0.8828 | 69.93 | 472 | 0.9914 | 0.5648 | | 0.8828 | 70.96 | 479 | 0.9838 | 0.5509 | | 0.8874 | 72.0 | 486 | 0.9646 | 0.5741 | | 0.8723 | 72.89 | 492 | 1.0682 | 0.5324 | | 0.8723 | 73.93 | 499 | 1.0629 | 0.5417 | | 0.8953 | 74.96 | 506 | 0.9770 | 0.5648 | | 0.879 | 76.0 | 513 | 1.0038 | 0.5787 | | 0.879 | 76.89 | 519 | 1.0529 | 0.5648 | | 0.896 | 77.93 | 526 | 1.0300 | 0.5602 | | 0.8519 | 78.96 | 533 | 1.0451 | 0.5463 | | 0.8414 | 80.0 | 540 | 1.0755 | 0.5509 | | 0.8414 | 80.89 | 546 | 1.0287 | 0.5556 | | 0.8342 | 81.93 | 553 | 1.0140 | 0.5602 | | 0.8653 | 82.96 | 560 | 1.0787 | 0.5463 | | 0.8653 | 84.0 | 567 | 1.0762 | 0.5509 | | 0.8357 | 84.89 | 573 | 1.0307 | 0.5741 | | 0.8455 | 85.93 | 580 | 1.0171 | 0.5648 | | 0.8455 | 86.96 | 587 | 0.9886 | 0.5880 | | 0.8238 | 88.0 | 594 | 0.9806 | 0.5741 | | 0.8613 | 88.89 | 600 | 1.0177 | 0.5833 | | 0.8613 | 89.93 | 607 | 1.0273 | 0.5602 | | 0.8265 | 90.96 | 614 | 0.9857 | 0.5926 | | 0.831 | 92.0 | 621 | 0.9701 | 0.5972 | | 0.831 | 92.89 | 627 | 0.9726 | 0.5972 | | 0.8247 | 93.93 | 634 | 0.9765 | 0.5880 | | 0.8041 | 94.96 | 641 | 0.9801 | 0.5926 | | 0.8041 | 96.0 | 648 | 0.9796 | 0.5926 | | 0.8387 | 96.89 | 654 | 0.9790 | 0.5972 | | 0.7906 | 97.78 | 660 | 0.9783 | 0.5972 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3