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--- |
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library_name: transformers |
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language: |
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- bem |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- BIG_C/Bemba |
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metrics: |
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- wer |
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model-index: |
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- name: facebook/mms-1b-all |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: BIG_C |
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type: BIG_C/Bemba |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4635265611806601 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# facebook/mms-1b-all |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIG_C dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5796 |
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- Model Preparation Time: 0.0177 |
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- Wer: 0.4635 |
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- Cer: 0.1168 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:| |
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| 5.2767 | 1.0 | 154 | 0.6576 | 0.0177 | 0.5943 | 0.1359 | |
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| 0.7588 | 2.0 | 308 | 0.6085 | 0.0177 | 0.5476 | 0.1268 | |
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| 0.7192 | 3.0 | 462 | 0.5971 | 0.0177 | 0.5313 | 0.1248 | |
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| 0.7048 | 4.0 | 616 | 0.5944 | 0.0177 | 0.5432 | 0.1246 | |
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| 0.6911 | 5.0 | 770 | 0.5889 | 0.0177 | 0.5271 | 0.1226 | |
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| 0.679 | 6.0 | 924 | 0.5702 | 0.0177 | 0.5111 | 0.1205 | |
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| 0.6623 | 7.0 | 1078 | 0.5724 | 0.0177 | 0.5046 | 0.1201 | |
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| 0.65 | 8.0 | 1232 | 0.5605 | 0.0177 | 0.5054 | 0.1209 | |
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| 0.6421 | 9.0 | 1386 | 0.5515 | 0.0177 | 0.4993 | 0.1178 | |
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| 0.626 | 10.0 | 1540 | 0.5518 | 0.0177 | 0.4914 | 0.1166 | |
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| 0.5999 | 11.0 | 1694 | 0.5358 | 0.0177 | 0.4910 | 0.1161 | |
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| 0.5824 | 12.0 | 1848 | 0.5425 | 0.0177 | 0.5016 | 0.1226 | |
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| 0.5723 | 13.0 | 2002 | 0.5325 | 0.0177 | 0.5071 | 0.1195 | |
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| 0.5576 | 14.0 | 2156 | 0.5437 | 0.0177 | 0.4880 | 0.1160 | |
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| 0.5498 | 15.0 | 2310 | 0.5725 | 0.0177 | 0.5341 | 0.1466 | |
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| 0.5383 | 16.0 | 2464 | 0.5814 | 0.0177 | 0.4721 | 0.1141 | |
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| 0.5283 | 17.0 | 2618 | 0.5483 | 0.0177 | 0.4819 | 0.1170 | |
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| 0.5145 | 18.0 | 2772 | 0.5297 | 0.0177 | 0.4931 | 0.1237 | |
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| 0.4977 | 19.0 | 2926 | 0.5283 | 0.0177 | 0.4889 | 0.1208 | |
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| 0.4913 | 20.0 | 3080 | 0.5365 | 0.0177 | 0.4776 | 0.1236 | |
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| 0.4822 | 21.0 | 3234 | 0.5562 | 0.0177 | 0.4708 | 0.1149 | |
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| 0.4768 | 22.0 | 3388 | 0.5493 | 0.0177 | 0.4804 | 0.1160 | |
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| 0.4598 | 23.0 | 3542 | 0.5574 | 0.0177 | 0.4736 | 0.1165 | |
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| 0.4558 | 24.0 | 3696 | 0.5340 | 0.0177 | 0.4766 | 0.1195 | |
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| 0.4516 | 25.0 | 3850 | 0.5703 | 0.0177 | 0.4787 | 0.1143 | |
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| 0.44 | 26.0 | 4004 | 0.5329 | 0.0177 | 0.4662 | 0.1144 | |
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| 0.4322 | 27.0 | 4158 | 0.5790 | 0.0177 | 0.4738 | 0.1136 | |
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| 0.4264 | 28.0 | 4312 | 0.5581 | 0.0177 | 0.4729 | 0.1133 | |
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| 0.4193 | 29.0 | 4466 | 0.5655 | 0.0177 | 0.4642 | 0.1144 | |
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| 0.4115 | 30.0 | 4620 | 0.5521 | 0.0177 | 0.4657 | 0.1173 | |
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| 0.4046 | 31.0 | 4774 | 0.5370 | 0.0177 | 0.4626 | 0.1139 | |
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| 0.4037 | 32.0 | 4928 | 0.5517 | 0.0177 | 0.4753 | 0.1173 | |
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| 0.4016 | 33.0 | 5082 | 0.5733 | 0.0177 | 0.4566 | 0.1119 | |
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| 0.3928 | 34.0 | 5236 | 0.5542 | 0.0177 | 0.4715 | 0.1164 | |
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| 0.3827 | 35.0 | 5390 | 0.5504 | 0.0177 | 0.4587 | 0.1132 | |
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| 0.3828 | 36.0 | 5544 | 0.5541 | 0.0177 | 0.4587 | 0.1126 | |
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| 0.3788 | 37.0 | 5698 | 0.5548 | 0.0177 | 0.4551 | 0.1121 | |
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| 0.371 | 38.0 | 5852 | 0.5574 | 0.0177 | 0.4543 | 0.1131 | |
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| 0.3712 | 39.0 | 6006 | 0.5709 | 0.0177 | 0.4600 | 0.1114 | |
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| 0.3631 | 40.0 | 6160 | 0.5783 | 0.0177 | 0.4655 | 0.1174 | |
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| 0.3561 | 41.0 | 6314 | 0.5753 | 0.0177 | 0.4628 | 0.1151 | |
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| 0.3518 | 42.0 | 6468 | 0.5695 | 0.0177 | 0.4691 | 0.1188 | |
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| 0.3472 | 43.0 | 6622 | 0.5802 | 0.0177 | 0.4619 | 0.1119 | |
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| 0.3423 | 44.0 | 6776 | 0.5796 | 0.0177 | 0.4636 | 0.1146 | |
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| 0.3352 | 45.0 | 6930 | 0.5940 | 0.0177 | 0.4585 | 0.1145 | |
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| 0.3335 | 46.0 | 7084 | 0.5915 | 0.0177 | 0.4679 | 0.1189 | |
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| 0.3294 | 47.0 | 7238 | 0.5885 | 0.0177 | 0.4664 | 0.1165 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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