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library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec-xlsr-grain-lg_cv_only
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: lg
split: test[:10%]
args: lg
metrics:
- name: Wer
type: wer
value: 0.22608421715845847
---
<!-- 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-grain-lg_cv_only
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7249
- Wer: 0.2261
- Cer: 0.0663
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 1.7903 | 1.0 | 2221 | 0.4623 | 0.4252 | 0.1113 |
| 0.6251 | 2.0 | 4442 | 0.4990 | 0.3665 | 0.1008 |
| 0.528 | 3.0 | 6663 | 0.3703 | 0.3417 | 0.0958 |
| 0.4766 | 4.0 | 8884 | 0.3617 | 0.3209 | 0.0899 |
| 0.4419 | 5.0 | 11105 | 0.3458 | 0.3002 | 0.0853 |
| 0.4112 | 6.0 | 13326 | 0.3946 | 0.3075 | 0.0856 |
| 0.3909 | 7.0 | 15547 | 0.3615 | 0.2984 | 0.0854 |
| 0.3714 | 8.0 | 17768 | 0.3903 | 0.2916 | 0.0820 |
| 0.3537 | 9.0 | 19989 | 0.4078 | 0.2935 | 0.0829 |
| 0.3375 | 10.0 | 22210 | 0.3634 | 0.2886 | 0.0849 |
| 0.3205 | 11.0 | 24431 | 0.3772 | 0.2892 | 0.0801 |
| 0.307 | 12.0 | 26652 | 0.3912 | 0.2810 | 0.0785 |
| 0.2961 | 13.0 | 28873 | 0.3527 | 0.2801 | 0.0803 |
| 0.2833 | 14.0 | 31094 | 0.3524 | 0.2892 | 0.0824 |
| 0.272 | 15.0 | 33315 | 0.3955 | 0.2834 | 0.0809 |
| 0.2608 | 16.0 | 35536 | 0.3707 | 0.2805 | 0.0799 |
| 0.2524 | 17.0 | 37757 | 0.4076 | 0.2834 | 0.0792 |
| 0.2445 | 18.0 | 39978 | 0.4205 | 0.2768 | 0.0790 |
| 0.2304 | 19.0 | 42199 | 0.4796 | 0.2809 | 0.0802 |
| 0.2266 | 20.0 | 44420 | 0.3985 | 0.2768 | 0.0799 |
| 0.2154 | 21.0 | 46641 | 0.4254 | 0.2748 | 0.0788 |
| 0.2098 | 22.0 | 48862 | 0.4124 | 0.2703 | 0.0776 |
| 0.1972 | 23.0 | 51083 | 0.3918 | 0.2728 | 0.0783 |
| 0.1925 | 24.0 | 53304 | 0.4703 | 0.2707 | 0.0783 |
| 0.1842 | 25.0 | 55525 | 0.4228 | 0.2724 | 0.0786 |
| 0.1775 | 26.0 | 57746 | 0.4272 | 0.2765 | 0.0784 |
| 0.1729 | 27.0 | 59967 | 0.4161 | 0.2729 | 0.0780 |
| 0.1656 | 28.0 | 62188 | 0.4232 | 0.2648 | 0.0777 |
| 0.1565 | 29.0 | 64409 | 0.4187 | 0.2691 | 0.0780 |
| 0.1555 | 30.0 | 66630 | 0.4280 | 0.2609 | 0.0757 |
| 0.148 | 31.0 | 68851 | 0.4350 | 0.2669 | 0.0778 |
| 0.1443 | 32.0 | 71072 | 0.4718 | 0.2676 | 0.0782 |
| 0.1407 | 33.0 | 73293 | 0.4996 | 0.2723 | 0.0768 |
| 0.1366 | 34.0 | 75514 | 0.4620 | 0.2701 | 0.0770 |
| 0.1321 | 35.0 | 77735 | 0.5067 | 0.2691 | 0.0762 |
| 0.1288 | 36.0 | 79956 | 0.4975 | 0.2613 | 0.0747 |
| 0.1273 | 37.0 | 82177 | 0.4832 | 0.2584 | 0.0744 |
| 0.1218 | 38.0 | 84398 | 0.5097 | 0.2587 | 0.0759 |
| 0.1183 | 39.0 | 86619 | 0.5145 | 0.2657 | 0.0759 |
| 0.1174 | 40.0 | 88840 | 0.5500 | 0.2599 | 0.0753 |
| 0.1142 | 41.0 | 91061 | 0.5112 | 0.2674 | 0.0761 |
| 0.1107 | 42.0 | 93282 | 0.5121 | 0.2615 | 0.0745 |
| 0.1088 | 43.0 | 95503 | 0.5215 | 0.2605 | 0.0753 |
| 0.1056 | 44.0 | 97724 | 0.4900 | 0.2548 | 0.0735 |
| 0.1046 | 45.0 | 99945 | 0.4887 | 0.2565 | 0.0729 |
| 0.1027 | 46.0 | 102166 | 0.5140 | 0.2480 | 0.0712 |
| 0.0995 | 47.0 | 104387 | 0.5110 | 0.2552 | 0.0726 |
| 0.0967 | 48.0 | 106608 | 0.5228 | 0.2562 | 0.0731 |
| 0.0938 | 49.0 | 108829 | 0.4963 | 0.2464 | 0.0702 |
| 0.0934 | 50.0 | 111050 | 0.5024 | 0.2496 | 0.0710 |
| 0.0898 | 51.0 | 113271 | 0.6114 | 0.2563 | 0.0747 |
| 0.0891 | 52.0 | 115492 | 0.5993 | 0.2575 | 0.0728 |
| 0.0864 | 53.0 | 117713 | 0.6181 | 0.2517 | 0.0721 |
| 0.0849 | 54.0 | 119934 | 0.7066 | 0.2550 | 0.0739 |
| 0.0829 | 55.0 | 122155 | 0.5745 | 0.2491 | 0.0720 |
| 0.0811 | 56.0 | 124376 | 0.5194 | 0.2438 | 0.0701 |
| 0.0804 | 57.0 | 126597 | 0.6308 | 0.2474 | 0.0716 |
| 0.0773 | 58.0 | 128818 | 0.5573 | 0.2428 | 0.0698 |
| 0.076 | 59.0 | 131039 | 0.5476 | 0.2462 | 0.0708 |
| 0.0748 | 60.0 | 133260 | 0.5976 | 0.2440 | 0.0717 |
| 0.0742 | 61.0 | 135481 | 0.6067 | 0.2448 | 0.0714 |
| 0.0725 | 62.0 | 137702 | 0.5574 | 0.2439 | 0.0702 |
| 0.0711 | 63.0 | 139923 | 0.5936 | 0.2409 | 0.0711 |
| 0.0698 | 64.0 | 142144 | 0.6039 | 0.2385 | 0.0715 |
| 0.0683 | 65.0 | 144365 | 0.5694 | 0.2417 | 0.0716 |
| 0.066 | 66.0 | 146586 | 0.6021 | 0.2415 | 0.0701 |
| 0.0653 | 67.0 | 148807 | 0.5839 | 0.2428 | 0.0702 |
| 0.0633 | 68.0 | 151028 | 0.5638 | 0.2353 | 0.0678 |
| 0.0621 | 69.0 | 153249 | 0.5731 | 0.2412 | 0.0696 |
| 0.0613 | 70.0 | 155470 | 0.6641 | 0.2430 | 0.0713 |
| 0.0606 | 71.0 | 157691 | 0.5871 | 0.2396 | 0.0693 |
| 0.0576 | 72.0 | 159912 | 0.6178 | 0.2424 | 0.0708 |
| 0.057 | 73.0 | 162133 | 0.6113 | 0.2356 | 0.0680 |
| 0.0558 | 74.0 | 164354 | 0.5890 | 0.2328 | 0.0683 |
| 0.0555 | 75.0 | 166575 | 0.6186 | 0.2427 | 0.0701 |
| 0.0542 | 76.0 | 168796 | 0.6637 | 0.2438 | 0.0709 |
| 0.0526 | 77.0 | 171017 | 0.6172 | 0.2449 | 0.0701 |
| 0.0519 | 78.0 | 173238 | 0.6267 | 0.2384 | 0.0710 |
| 0.0505 | 79.0 | 175459 | 0.6162 | 0.2366 | 0.0681 |
| 0.0494 | 80.0 | 177680 | 0.6146 | 0.2396 | 0.0688 |
| 0.0486 | 81.0 | 179901 | 0.5919 | 0.2316 | 0.0678 |
| 0.0482 | 82.0 | 182122 | 0.6668 | 0.2363 | 0.0716 |
| 0.0467 | 83.0 | 184343 | 0.6901 | 0.2288 | 0.0682 |
| 0.0457 | 84.0 | 186564 | 0.6474 | 0.2365 | 0.0688 |
| 0.0452 | 85.0 | 188785 | 0.6615 | 0.2352 | 0.0697 |
| 0.0434 | 86.0 | 191006 | 0.6998 | 0.2311 | 0.0683 |
| 0.0423 | 87.0 | 193227 | 0.6605 | 0.2279 | 0.0674 |
| 0.0423 | 88.0 | 195448 | 0.7154 | 0.2361 | 0.0709 |
| 0.0408 | 89.0 | 197669 | 0.6706 | 0.2260 | 0.0658 |
| 0.041 | 90.0 | 199890 | 0.7034 | 0.2263 | 0.0668 |
| 0.0391 | 91.0 | 202111 | 0.6943 | 0.2258 | 0.0659 |
| 0.0387 | 92.0 | 204332 | 0.6964 | 0.2259 | 0.0660 |
| 0.0378 | 93.0 | 206553 | 0.6930 | 0.2278 | 0.0661 |
| 0.0368 | 94.0 | 208774 | 0.7106 | 0.2247 | 0.0661 |
| 0.0372 | 95.0 | 210995 | 0.7001 | 0.2245 | 0.0656 |
| 0.0366 | 96.0 | 213216 | 0.7010 | 0.2247 | 0.0658 |
| 0.0357 | 97.0 | 215437 | 0.7196 | 0.2228 | 0.0661 |
| 0.0351 | 98.0 | 217658 | 0.7143 | 0.2238 | 0.0657 |
| 0.0356 | 99.0 | 219879 | 0.7230 | 0.2262 | 0.0662 |
| 0.0352 | 100.0 | 222100 | 0.7249 | 0.2261 | 0.0663 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
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