--- library_name: transformers language: - bem license: cc-by-nc-4.0 base_model: facebook/mms-1b-all tags: - generated_from_trainer datasets: - BIG_C/Bemba metrics: - wer model-index: - name: facebook/mms-1b-all results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: BIG_C type: BIG_C/Bemba metrics: - name: Wer type: wer value: 0.4668925293764474 --- # facebook/mms-1b-all This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIG_C dataset. It achieves the following results on the evaluation set: - Loss: 0.4083 - Model Preparation Time: 0.011 - Wer: 0.4669 - Cer: 0.0879 ## 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: 0.0003 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:| | 2.6526 | 1.0 | 310 | 0.6127 | 0.011 | 0.5519 | 0.1287 | | 0.7346 | 2.0 | 620 | 0.5850 | 0.011 | 0.5399 | 0.1242 | | 0.7091 | 3.0 | 930 | 0.5726 | 0.011 | 0.5136 | 0.1200 | | 0.6967 | 4.0 | 1240 | 0.5618 | 0.011 | 0.5028 | 0.1189 | | 0.6769 | 5.0 | 1550 | 0.5520 | 0.011 | 0.4967 | 0.1176 | | 0.6626 | 6.0 | 1860 | 0.5432 | 0.011 | 0.4935 | 0.1158 | | 0.6428 | 7.0 | 2170 | 0.5231 | 0.011 | 0.4930 | 0.1178 | | 0.6229 | 8.0 | 2480 | 0.5320 | 0.011 | 0.4798 | 0.1134 | | 0.6081 | 9.0 | 2790 | 0.5168 | 0.011 | 0.4842 | 0.1155 | | 0.5939 | 10.0 | 3100 | 0.5067 | 0.011 | 0.4835 | 0.1171 | | 0.5807 | 11.0 | 3410 | 0.5217 | 0.011 | 0.4682 | 0.1106 | | 0.5705 | 12.0 | 3720 | 0.5030 | 0.011 | 0.4797 | 0.1172 | | 0.5584 | 13.0 | 4030 | 0.4976 | 0.011 | 0.4689 | 0.1108 | | 0.5512 | 14.0 | 4340 | 0.4981 | 0.011 | 0.4766 | 0.1188 | | 0.5444 | 15.0 | 4650 | 0.5096 | 0.011 | 0.4594 | 0.1090 | | 0.5333 | 16.0 | 4960 | 0.4995 | 0.011 | 0.4641 | 0.1111 | | 0.5204 | 17.0 | 5270 | 0.5116 | 0.011 | 0.4555 | 0.1086 | | 0.513 | 18.0 | 5580 | 0.4998 | 0.011 | 0.4590 | 0.1121 | | 0.5049 | 19.0 | 5890 | 0.4997 | 0.011 | 0.4557 | 0.1109 | | 0.5011 | 20.0 | 6200 | 0.4960 | 0.011 | 0.4718 | 0.1198 | | 0.4888 | 21.0 | 6510 | 0.5026 | 0.011 | 0.4579 | 0.1126 | | 0.491 | 22.0 | 6820 | 0.5145 | 0.011 | 0.4474 | 0.1071 | | 0.4804 | 23.0 | 7130 | 0.5026 | 0.011 | 0.4510 | 0.1053 | | 0.4727 | 24.0 | 7440 | 0.5218 | 0.011 | 0.4416 | 0.1052 | | 0.4666 | 25.0 | 7750 | 0.4990 | 0.011 | 0.4593 | 0.1148 | | 0.4614 | 26.0 | 8060 | 0.5103 | 0.011 | 0.4446 | 0.1053 | | 0.4546 | 27.0 | 8370 | 0.5019 | 0.011 | 0.4479 | 0.1086 | | 0.45 | 28.0 | 8680 | 0.4946 | 0.011 | 0.4485 | 0.1086 | | 0.4443 | 29.0 | 8990 | 0.4997 | 0.011 | 0.4389 | 0.1051 | | 0.4369 | 30.0 | 9300 | 0.5063 | 0.011 | 0.4376 | 0.1045 | | 0.4302 | 31.0 | 9610 | 0.5071 | 0.011 | 0.4448 | 0.1062 | | 0.4227 | 32.0 | 9920 | 0.5074 | 0.011 | 0.4435 | 0.1096 | | 0.4226 | 33.0 | 10230 | 0.5092 | 0.011 | 0.4477 | 0.1110 | | 0.4191 | 34.0 | 10540 | 0.5107 | 0.011 | 0.4519 | 0.1109 | | 0.4128 | 35.0 | 10850 | 0.5162 | 0.011 | 0.4412 | 0.1068 | | 0.408 | 36.0 | 11160 | 0.5201 | 0.011 | 0.4388 | 0.1074 | | 0.4022 | 37.0 | 11470 | 0.5138 | 0.011 | 0.4436 | 0.1088 | | 0.3979 | 38.0 | 11780 | 0.5331 | 0.011 | 0.4386 | 0.1062 | | 0.3937 | 39.0 | 12090 | 0.5225 | 0.011 | 0.4446 | 0.1124 | | 0.3905 | 40.0 | 12400 | 0.5200 | 0.011 | 0.4355 | 0.1065 | | 0.3846 | 41.0 | 12710 | 0.5115 | 0.011 | 0.4394 | 0.1092 | | 0.3827 | 42.0 | 13020 | 0.5169 | 0.011 | 0.4458 | 0.1131 | | 0.3797 | 43.0 | 13330 | 0.5237 | 0.011 | 0.4387 | 0.1088 | | 0.3729 | 44.0 | 13640 | 0.5431 | 0.011 | 0.4318 | 0.1057 | | 0.3694 | 45.0 | 13950 | 0.5375 | 0.011 | 0.4318 | 0.1060 | | 0.3656 | 46.0 | 14260 | 0.5301 | 0.011 | 0.4409 | 0.1099 | | 0.3618 | 47.0 | 14570 | 0.5422 | 0.011 | 0.4460 | 0.1146 | | 0.3572 | 48.0 | 14880 | 0.5404 | 0.011 | 0.4395 | 0.1084 | | 0.3523 | 49.0 | 15190 | 0.5442 | 0.011 | 0.4421 | 0.1112 | | 0.3514 | 50.0 | 15500 | 0.5561 | 0.011 | 0.4345 | 0.1072 | | 0.3473 | 51.0 | 15810 | 0.5549 | 0.011 | 0.4393 | 0.1113 | | 0.3443 | 52.0 | 16120 | 0.5469 | 0.011 | 0.4424 | 0.1127 | | 0.3412 | 53.0 | 16430 | 0.5624 | 0.011 | 0.4529 | 0.1165 | | 0.3343 | 54.0 | 16740 | 0.5548 | 0.011 | 0.4491 | 0.1143 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 3.1.0 - Tokenizers 0.20.1