--- license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-Phoneme results: [] --- # wav2vec2-Phoneme This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2842 - Wer: 0.1281 ## 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: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 30 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:-----:|:---------------:|:------:| | 2.1769 | 0.2954 | 100 | 2.1463 | 0.9564 | | 2.1285 | 0.5908 | 200 | 2.0959 | 0.9575 | | 1.8989 | 0.8863 | 300 | 1.5997 | 0.9022 | | 1.1123 | 1.1817 | 400 | 0.6782 | 0.4093 | | 0.618 | 1.4771 | 500 | 0.3548 | 0.1544 | | 0.4993 | 1.7725 | 600 | 0.3039 | 0.1331 | | 0.4425 | 2.0679 | 700 | 0.2688 | 0.1169 | | 0.363 | 2.3634 | 800 | 0.2419 | 0.1108 | | 0.3507 | 2.6588 | 900 | 0.2220 | 0.1039 | | 0.3282 | 2.9542 | 1000 | 0.1999 | 0.1001 | | 0.2887 | 3.2496 | 1100 | 0.2044 | 0.0974 | | 0.3104 | 3.5451 | 1200 | 0.1950 | 0.0994 | | 0.2976 | 3.8405 | 1300 | 0.2005 | 0.0969 | | 0.2617 | 4.1359 | 1400 | 0.1907 | 0.0962 | | 0.2783 | 4.4313 | 1500 | 0.1886 | 0.0936 | | 0.2533 | 4.7267 | 1600 | 0.1845 | 0.0938 | | 0.2501 | 5.0222 | 1700 | 0.1759 | 0.0926 | | 0.2261 | 5.3176 | 1800 | 0.1789 | 0.0896 | | 0.2112 | 5.6130 | 1900 | 0.1824 | 0.0891 | | 0.2162 | 5.9084 | 2000 | 0.1715 | 0.0886 | | 0.2098 | 6.2038 | 2100 | 0.1761 | 0.0902 | | 0.2133 | 6.4993 | 2200 | 0.1747 | 0.0896 | | 0.2174 | 6.7947 | 2300 | 0.1753 | 0.0892 | | 0.2033 | 7.0901 | 2400 | 0.1729 | 0.0886 | | 0.2167 | 7.3855 | 2500 | 0.1749 | 0.0889 | | 0.2001 | 7.6809 | 2600 | 0.1650 | 0.0874 | | 0.1874 | 7.9764 | 2700 | 0.1656 | 0.0872 | | 0.1846 | 8.2718 | 2800 | 0.1674 | 0.0873 | | 0.1927 | 8.5672 | 2900 | 0.1595 | 0.0863 | | 0.1672 | 8.8626 | 3000 | 0.1552 | 0.0849 | | 0.1741 | 9.1581 | 3100 | 0.1659 | 0.0868 | | 0.1753 | 9.4535 | 3200 | 0.1615 | 0.0862 | | 0.1825 | 9.7489 | 3300 | 0.1623 | 0.0862 | | 0.166 | 10.0443 | 3400 | 0.1584 | 0.0865 | | 0.1762 | 10.3397 | 3500 | 0.1573 | 0.0850 | | 0.1744 | 10.6352 | 3600 | 0.1537 | 0.0863 | | 0.1786 | 10.9306 | 3700 | 0.1522 | 0.0840 | | 0.1731 | 11.2260 | 3800 | 0.1645 | 0.0851 | | 0.1929 | 11.5214 | 3900 | 0.1785 | 0.0851 | | 0.2047 | 11.8168 | 4000 | 0.1844 | 0.0860 | | 0.255 | 12.1123 | 4100 | 0.2305 | 0.0911 | | 0.2771 | 12.4077 | 4200 | 0.2311 | 0.0886 | | 0.2742 | 12.7031 | 4300 | 0.2605 | 0.0901 | | 0.3879 | 12.9985 | 4400 | 0.2886 | 0.0965 | | 0.3655 | 13.2939 | 4500 | 0.2897 | 0.0933 | | 0.3693 | 13.5894 | 4600 | 0.2936 | 0.0960 | | 0.3999 | 13.8848 | 4700 | 0.2905 | 0.1059 | | 0.4286 | 14.1802 | 4800 | 0.3424 | 0.1025 | | 0.574 | 14.4756 | 4900 | 0.3891 | 0.1135 | | 0.5753 | 14.7710 | 5000 | 0.3912 | 0.1276 | | 0.5225 | 15.0665 | 5100 | 0.4248 | 0.1151 | | 0.4785 | 15.3619 | 5200 | 0.3332 | 0.1287 | | 0.5733 | 15.6573 | 5300 | 0.3999 | 0.1261 | | 0.5471 | 15.9527 | 5400 | 0.4144 | 0.1293 | | 0.5527 | 16.2482 | 5500 | 0.3580 | 0.1160 | | 0.6322 | 16.5436 | 5600 | 0.5158 | 0.1794 | | 0.6867 | 16.8390 | 5700 | 0.4731 | 0.1411 | | 0.606 | 17.1344 | 5800 | 0.3812 | 0.1305 | | 0.5376 | 17.4298 | 5900 | 0.3505 | 0.1206 | | 0.5035 | 17.7253 | 6000 | 0.3251 | 0.1199 | | 0.469 | 18.0207 | 6100 | 0.3092 | 0.1172 | | 0.4544 | 18.3161 | 6200 | 0.3030 | 0.1185 | | 0.4288 | 18.6115 | 6300 | 0.2915 | 0.1183 | | 0.4457 | 18.9069 | 6400 | 0.2834 | 0.1203 | | 0.408 | 19.2024 | 6500 | 0.2765 | 0.1212 | | 0.4182 | 19.4978 | 6600 | 0.2741 | 0.1205 | | 0.4117 | 19.7932 | 6700 | 0.2705 | 0.1209 | | 0.4131 | 20.0886 | 6800 | 0.2725 | 0.1230 | | 0.4034 | 20.3840 | 6900 | 0.2713 | 0.1218 | | 0.4048 | 20.6795 | 7000 | 0.2707 | 0.1226 | | 0.4199 | 20.9749 | 7100 | 0.2695 | 0.1221 | | 0.4286 | 21.2703 | 7200 | 0.2709 | 0.1239 | | 0.3968 | 21.5657 | 7300 | 0.2699 | 0.1230 | | 0.4071 | 21.8612 | 7400 | 0.2705 | 0.1254 | | 0.4178 | 22.1566 | 7500 | 0.2701 | 0.1252 | | 0.396 | 22.4520 | 7600 | 0.2702 | 0.1252 | | 0.4255 | 22.7474 | 7700 | 0.2701 | 0.1249 | | 0.4239 | 23.0428 | 7800 | 0.2716 | 0.1254 | | 0.4153 | 23.3383 | 7900 | 0.2729 | 0.1264 | | 0.4265 | 23.6337 | 8000 | 0.2726 | 0.1264 | | 0.4221 | 23.9291 | 8100 | 0.2737 | 0.1266 | | 0.4268 | 24.2245 | 8200 | 0.2751 | 0.1269 | | 0.4207 | 24.5199 | 8300 | 0.2761 | 0.1273 | | 0.3872 | 24.8154 | 8400 | 0.2764 | 0.1273 | | 0.4004 | 25.1108 | 8500 | 0.2786 | 0.1276 | | 0.4096 | 25.4062 | 8600 | 0.2798 | 0.1276 | | 0.4542 | 25.7016 | 8700 | 0.2803 | 0.1274 | | 0.4361 | 25.9970 | 8800 | 0.2818 | 0.1276 | | 0.4454 | 26.2925 | 8900 | 0.2826 | 0.1277 | | 0.4204 | 26.5879 | 9000 | 0.2842 | 0.1281 | | 0.4423 | 26.8833 | 9100 | 0.2841 | 0.1280 | | 0.4333 | 27.1787 | 9200 | 0.2845 | 0.1282 | | 0.4036 | 27.4742 | 9300 | 0.2844 | 0.1281 | | 0.4203 | 27.7696 | 9400 | 0.2844 | 0.1281 | | 0.4321 | 28.0650 | 9500 | 0.2842 | 0.1281 | | 0.4251 | 28.3604 | 9600 | 0.2842 | 0.1281 | | 0.4122 | 28.6558 | 9700 | 0.2841 | 0.1281 | | 0.424 | 28.9513 | 9800 | 0.2841 | 0.1280 | | 0.4404 | 29.2467 | 9900 | 0.2842 | 0.1281 | | 0.4174 | 29.5421 | 10000 | 0.2842 | 0.1281 | | 0.4432 | 29.8375 | 10100 | 0.2842 | 0.1281 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.2.1+cu121 - Datasets 2.19.1.dev0 - Tokenizers 0.19.1