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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec-xlsr-cv-grain-lg_both
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec-xlsr-cv-grain-lg_both
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0871
- Wer: 0.0289
- Cer: 0.0079
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 1.9082 | 1.0 | 2703 | 0.2081 | 0.2630 | 0.0539 |
| 0.6172 | 2.0 | 5406 | 0.1523 | 0.1853 | 0.0386 |
| 0.5149 | 3.0 | 8109 | 0.1235 | 0.1432 | 0.0307 |
| 0.4589 | 4.0 | 10812 | 0.1207 | 0.1297 | 0.0285 |
| 0.4226 | 5.0 | 13515 | 0.1007 | 0.1117 | 0.0238 |
| 0.3932 | 6.0 | 16218 | 0.0988 | 0.0979 | 0.0225 |
| 0.3706 | 7.0 | 18921 | 0.0916 | 0.0924 | 0.0212 |
| 0.3481 | 8.0 | 21624 | 0.0882 | 0.0881 | 0.0210 |
| 0.3291 | 9.0 | 24327 | 0.0856 | 0.0803 | 0.0185 |
| 0.3131 | 10.0 | 27030 | 0.0806 | 0.0777 | 0.0182 |
| 0.2997 | 11.0 | 29733 | 0.0767 | 0.0733 | 0.0175 |
| 0.2851 | 12.0 | 32436 | 0.0749 | 0.0742 | 0.0178 |
| 0.2745 | 13.0 | 35139 | 0.0738 | 0.0636 | 0.0161 |
| 0.2628 | 14.0 | 37842 | 0.0818 | 0.0749 | 0.0177 |
| 0.2487 | 15.0 | 40545 | 0.0750 | 0.0699 | 0.0162 |
| 0.2389 | 16.0 | 43248 | 0.0682 | 0.0586 | 0.0145 |
| 0.2299 | 17.0 | 45951 | 0.0675 | 0.0590 | 0.0137 |
| 0.22 | 18.0 | 48654 | 0.0715 | 0.0562 | 0.0140 |
| 0.2102 | 19.0 | 51357 | 0.0757 | 0.0534 | 0.0134 |
| 0.202 | 20.0 | 54060 | 0.0785 | 0.0586 | 0.0149 |
| 0.195 | 21.0 | 56763 | 0.0731 | 0.0590 | 0.0136 |
| 0.186 | 22.0 | 59466 | 0.0750 | 0.0566 | 0.0136 |
| 0.1797 | 23.0 | 62169 | 0.0746 | 0.0523 | 0.0127 |
| 0.1713 | 24.0 | 64872 | 0.0739 | 0.0538 | 0.0132 |
| 0.1634 | 25.0 | 67575 | 0.0806 | 0.0514 | 0.0130 |
| 0.157 | 26.0 | 70278 | 0.0748 | 0.0532 | 0.0132 |
| 0.1521 | 27.0 | 72981 | 0.0774 | 0.0521 | 0.0133 |
| 0.1483 | 28.0 | 75684 | 0.0775 | 0.0501 | 0.0125 |
| 0.1424 | 29.0 | 78387 | 0.0772 | 0.0479 | 0.0122 |
| 0.1363 | 30.0 | 81090 | 0.0747 | 0.0453 | 0.0116 |
| 0.1322 | 31.0 | 83793 | 0.0801 | 0.0436 | 0.0116 |
| 0.1266 | 32.0 | 86496 | 0.0758 | 0.0473 | 0.0112 |
| 0.1234 | 33.0 | 89199 | 0.0691 | 0.0430 | 0.0107 |
| 0.1214 | 34.0 | 91902 | 0.0853 | 0.0458 | 0.0120 |
| 0.1178 | 35.0 | 94605 | 0.0805 | 0.0436 | 0.0107 |
| 0.1126 | 36.0 | 97308 | 0.0803 | 0.0436 | 0.0116 |
| 0.1119 | 37.0 | 100011 | 0.0744 | 0.0412 | 0.0105 |
| 0.1079 | 38.0 | 102714 | 0.0788 | 0.0421 | 0.0106 |
| 0.1039 | 39.0 | 105417 | 0.0802 | 0.0406 | 0.0105 |
| 0.1014 | 40.0 | 108120 | 0.0741 | 0.0367 | 0.0098 |
| 0.1 | 41.0 | 110823 | 0.0812 | 0.0401 | 0.0106 |
| 0.096 | 42.0 | 113526 | 0.0772 | 0.0410 | 0.0111 |
| 0.0937 | 43.0 | 116229 | 0.0782 | 0.0417 | 0.0106 |
| 0.0923 | 44.0 | 118932 | 0.0808 | 0.0404 | 0.0104 |
| 0.0894 | 45.0 | 121635 | 0.0725 | 0.0384 | 0.0097 |
| 0.0874 | 46.0 | 124338 | 0.0747 | 0.0351 | 0.0098 |
| 0.0856 | 47.0 | 127041 | 0.0761 | 0.0373 | 0.0100 |
| 0.0852 | 48.0 | 129744 | 0.0786 | 0.0393 | 0.0099 |
| 0.0821 | 49.0 | 132447 | 0.0766 | 0.0334 | 0.0092 |
| 0.0815 | 50.0 | 135150 | 0.0789 | 0.0365 | 0.0103 |
| 0.0798 | 51.0 | 137853 | 0.0813 | 0.0391 | 0.0101 |
| 0.0775 | 52.0 | 140556 | 0.0783 | 0.0341 | 0.0091 |
| 0.0755 | 53.0 | 143259 | 0.0793 | 0.0399 | 0.0105 |
| 0.0745 | 54.0 | 145962 | 0.0770 | 0.0408 | 0.0100 |
| 0.072 | 55.0 | 148665 | 0.0774 | 0.0349 | 0.0093 |
| 0.0708 | 56.0 | 151368 | 0.0811 | 0.0341 | 0.0091 |
| 0.0675 | 57.0 | 154071 | 0.0740 | 0.0321 | 0.0087 |
| 0.067 | 58.0 | 156774 | 0.0747 | 0.0321 | 0.0087 |
| 0.0657 | 59.0 | 159477 | 0.0721 | 0.0312 | 0.0085 |
| 0.0645 | 60.0 | 162180 | 0.0701 | 0.0341 | 0.0089 |
| 0.0631 | 61.0 | 164883 | 0.0788 | 0.0358 | 0.0090 |
| 0.0623 | 62.0 | 167586 | 0.0763 | 0.0312 | 0.0091 |
| 0.0614 | 63.0 | 170289 | 0.0777 | 0.0332 | 0.0087 |
| 0.0592 | 64.0 | 172992 | 0.0742 | 0.0319 | 0.0085 |
| 0.0576 | 65.0 | 175695 | 0.0755 | 0.0317 | 0.0085 |
| 0.0566 | 66.0 | 178398 | 0.0785 | 0.0347 | 0.0092 |
| 0.0565 | 67.0 | 181101 | 0.0794 | 0.0315 | 0.0086 |
| 0.0559 | 68.0 | 183804 | 0.0774 | 0.0317 | 0.0084 |
| 0.0534 | 69.0 | 186507 | 0.0814 | 0.0338 | 0.0088 |
| 0.0521 | 70.0 | 189210 | 0.0825 | 0.0330 | 0.0089 |
| 0.0514 | 71.0 | 191913 | 0.0781 | 0.0297 | 0.0081 |
| 0.0489 | 72.0 | 194616 | 0.0802 | 0.0293 | 0.0079 |
| 0.0496 | 73.0 | 197319 | 0.0799 | 0.0330 | 0.0086 |
| 0.0474 | 74.0 | 200022 | 0.0806 | 0.0299 | 0.0080 |
| 0.0479 | 75.0 | 202725 | 0.0789 | 0.0284 | 0.0080 |
| 0.0461 | 76.0 | 205428 | 0.0797 | 0.0308 | 0.0079 |
| 0.044 | 77.0 | 208131 | 0.0788 | 0.0284 | 0.0078 |
| 0.0444 | 78.0 | 210834 | 0.0830 | 0.0304 | 0.0083 |
| 0.0429 | 79.0 | 213537 | 0.0826 | 0.0312 | 0.0085 |
| 0.0423 | 80.0 | 216240 | 0.0845 | 0.0317 | 0.0087 |
| 0.041 | 81.0 | 218943 | 0.0862 | 0.0323 | 0.0085 |
| 0.0399 | 82.0 | 221646 | 0.0844 | 0.0297 | 0.0083 |
| 0.0402 | 83.0 | 224349 | 0.0884 | 0.0308 | 0.0084 |
| 0.0389 | 84.0 | 227052 | 0.0853 | 0.0276 | 0.0079 |
| 0.0372 | 85.0 | 229755 | 0.0839 | 0.0325 | 0.0082 |
| 0.0367 | 86.0 | 232458 | 0.0851 | 0.0282 | 0.0078 |
| 0.0358 | 87.0 | 235161 | 0.0836 | 0.0297 | 0.0081 |
| 0.0355 | 88.0 | 237864 | 0.0860 | 0.0295 | 0.0083 |
| 0.0347 | 89.0 | 240567 | 0.0848 | 0.0291 | 0.0081 |
| 0.0334 | 90.0 | 243270 | 0.0832 | 0.0280 | 0.0079 |
| 0.033 | 91.0 | 245973 | 0.0848 | 0.0282 | 0.0079 |
| 0.0329 | 92.0 | 248676 | 0.0852 | 0.0286 | 0.0082 |
| 0.0317 | 93.0 | 251379 | 0.0851 | 0.0291 | 0.0080 |
| 0.0314 | 94.0 | 254082 | 0.0873 | 0.0291 | 0.0080 |
| 0.0313 | 95.0 | 256785 | 0.0869 | 0.0284 | 0.0079 |
| 0.0305 | 96.0 | 259488 | 0.0853 | 0.0291 | 0.0080 |
| 0.03 | 97.0 | 262191 | 0.0862 | 0.0280 | 0.0077 |
| 0.0299 | 98.0 | 264894 | 0.0865 | 0.0282 | 0.0078 |
| 0.0286 | 99.0 | 267597 | 0.0871 | 0.0289 | 0.0079 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
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