metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- xtreme_s
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod10
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: xtreme_s
type: xtreme_s
config: fleurs.id_id
split: test
args: fleurs.id_id
metrics:
- name: Wer
type: wer
value: 0.9609339919173776
wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod10
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the xtreme_s dataset. It achieves the following results on the evaluation set:
- Loss: 2.5424
- Wer: 0.9609
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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Wer |
|---|---|---|---|---|
| 9.2693 | 1.0 | 39 | 3.1721 | 1.0 |
| 2.9485 | 2.0 | 78 | 2.8726 | 1.0 |
| 2.8943 | 3.0 | 117 | 2.8655 | 1.0 |
| 2.9036 | 4.0 | 156 | 2.8631 | 1.0 |
| 2.8869 | 5.0 | 195 | 2.8614 | 1.0 |
| 2.8802 | 6.0 | 234 | 2.8854 | 1.0 |
| 2.8802 | 7.0 | 273 | 2.8515 | 1.0 |
| 2.8706 | 8.0 | 312 | 2.8609 | 1.0 |
| 2.8712 | 9.0 | 351 | 2.8458 | 1.0 |
| 2.8583 | 10.0 | 390 | 2.8361 | 1.0 |
| 2.857 | 11.0 | 429 | 2.8355 | 1.0 |
| 2.8546 | 12.0 | 468 | 2.8439 | 1.0 |
| 2.8463 | 13.0 | 507 | 2.8348 | 1.0 |
| 2.8307 | 14.0 | 546 | 2.7596 | 1.0 |
| 2.7673 | 15.0 | 585 | 2.6289 | 1.0 |
| 2.5597 | 16.0 | 624 | 2.3411 | 1.0 |
| 2.224 | 17.0 | 663 | 2.0992 | 1.0 |
| 2.0145 | 18.0 | 702 | 1.7290 | 1.0 |
| 1.7274 | 19.0 | 741 | 1.5571 | 0.9954 |
| 1.6774 | 20.0 | 780 | 1.4439 | 0.9906 |
| 1.4585 | 21.0 | 819 | 1.3841 | 1.1238 |
| 1.342 | 22.0 | 858 | 1.2805 | 0.9662 |
| 1.215 | 23.0 | 897 | 1.2965 | 0.9628 |
| 1.188 | 24.0 | 936 | 1.2713 | 0.9659 |
| 1.1147 | 25.0 | 975 | 1.2936 | 1.0251 |
| 1.0374 | 26.0 | 1014 | 1.2900 | 0.9483 |
| 0.9352 | 27.0 | 1053 | 1.3671 | 0.9908 |
| 0.9249 | 28.0 | 1092 | 1.3018 | 0.9404 |
| 0.7973 | 29.0 | 1131 | 1.3253 | 0.9631 |
| 0.7451 | 30.0 | 1170 | 1.4314 | 1.0451 |
| 0.7391 | 31.0 | 1209 | 1.4553 | 0.9909 |
| 0.699 | 32.0 | 1248 | 1.5116 | 0.9487 |
| 0.5484 | 33.0 | 1287 | 1.5492 | 0.9829 |
| 0.5106 | 34.0 | 1326 | 1.6631 | 1.0674 |
| 0.5989 | 35.0 | 1365 | 1.6305 | 1.0150 |
| 0.464 | 36.0 | 1404 | 1.6285 | 0.9430 |
| 0.4925 | 37.0 | 1443 | 1.7208 | 1.0183 |
| 0.4206 | 38.0 | 1482 | 1.7476 | 1.0040 |
| 0.3848 | 39.0 | 1521 | 1.8125 | 1.0341 |
| 0.4057 | 40.0 | 1560 | 1.8245 | 0.9750 |
| 0.3978 | 41.0 | 1599 | 1.7153 | 0.9326 |
| 0.3806 | 42.0 | 1638 | 1.8650 | 1.0025 |
| 0.3376 | 43.0 | 1677 | 1.9067 | 0.9653 |
| 0.3798 | 44.0 | 1716 | 2.0028 | 0.9396 |
| 0.2902 | 45.0 | 1755 | 2.0901 | 0.9920 |
| 0.3324 | 46.0 | 1794 | 1.8935 | 0.9729 |
| 0.3241 | 47.0 | 1833 | 2.0133 | 1.0074 |
| 0.3055 | 48.0 | 1872 | 2.0352 | 0.9943 |
| 0.2927 | 49.0 | 1911 | 1.9539 | 1.0022 |
| 0.2729 | 50.0 | 1950 | 2.0982 | 0.9910 |
| 0.2569 | 51.0 | 1989 | 2.1607 | 0.9832 |
| 0.2683 | 52.0 | 2028 | 2.2544 | 0.9705 |
| 0.2685 | 53.0 | 2067 | 2.1528 | 0.9857 |
| 0.2757 | 54.0 | 2106 | 2.1648 | 0.9490 |
| 0.2379 | 55.0 | 2145 | 2.2498 | 0.9693 |
| 0.2501 | 56.0 | 2184 | 2.2509 | 1.0282 |
| 0.2347 | 57.0 | 2223 | 2.2095 | 0.9897 |
| 0.2697 | 58.0 | 2262 | 2.1933 | 0.9695 |
| 0.2255 | 59.0 | 2301 | 2.2140 | 0.9756 |
| 0.2071 | 60.0 | 2340 | 2.2364 | 0.9787 |
| 0.228 | 61.0 | 2379 | 2.3069 | 0.9551 |
| 0.2112 | 62.0 | 2418 | 2.3191 | 0.9769 |
| 0.2224 | 63.0 | 2457 | 2.2679 | 1.0025 |
| 0.2081 | 64.0 | 2496 | 2.2548 | 0.9660 |
| 0.2149 | 65.0 | 2535 | 2.1813 | 0.9720 |
| 0.2156 | 66.0 | 2574 | 2.0609 | 0.9633 |
| 0.1916 | 67.0 | 2613 | 2.4192 | 0.9594 |
| 0.2221 | 68.0 | 2652 | 2.3571 | 1.0186 |
| 0.1849 | 69.0 | 2691 | 2.3650 | 0.9705 |
| 0.1999 | 70.0 | 2730 | 2.3588 | 0.9700 |
| 0.2314 | 71.0 | 2769 | 2.5680 | 1.0693 |
| 0.1995 | 72.0 | 2808 | 2.3918 | 1.0490 |
| 0.1842 | 73.0 | 2847 | 2.3448 | 0.9706 |
| 0.1841 | 74.0 | 2886 | 2.3811 | 0.9945 |
| 0.1836 | 75.0 | 2925 | 2.4134 | 0.9659 |
| 0.1844 | 76.0 | 2964 | 2.3892 | 0.9657 |
| 0.1933 | 77.0 | 3003 | 2.3327 | 0.9606 |
| 0.1757 | 78.0 | 3042 | 2.4641 | 0.9702 |
| 0.1794 | 79.0 | 3081 | 2.4175 | 0.9535 |
| 0.1795 | 80.0 | 3120 | 2.3742 | 0.9503 |
| 0.1859 | 81.0 | 3159 | 2.5093 | 0.9508 |
| 0.1641 | 82.0 | 3198 | 2.4232 | 0.9647 |
| 0.195 | 83.0 | 3237 | 2.4070 | 0.9474 |
| 0.1712 | 84.0 | 3276 | 2.4726 | 0.9674 |
| 0.1882 | 85.0 | 3315 | 2.4682 | 0.9643 |
| 0.1746 | 86.0 | 3354 | 2.4826 | 0.9523 |
| 0.1655 | 87.0 | 3393 | 2.5652 | 0.9495 |
| 0.1895 | 88.0 | 3432 | 2.4967 | 0.9489 |
| 0.1659 | 89.0 | 3471 | 2.4620 | 0.9695 |
| 0.1618 | 90.0 | 3510 | 2.4974 | 0.9433 |
| 0.1559 | 91.0 | 3549 | 2.5137 | 0.9599 |
| 0.1646 | 92.0 | 3588 | 2.4645 | 0.9579 |
| 0.1599 | 93.0 | 3627 | 2.4751 | 0.9612 |
| 0.1735 | 94.0 | 3666 | 2.5473 | 0.9597 |
| 0.1571 | 95.0 | 3705 | 2.5158 | 0.9675 |
| 0.1606 | 96.0 | 3744 | 2.5234 | 0.9645 |
| 0.1499 | 97.0 | 3783 | 2.5328 | 0.9612 |
| 0.1571 | 98.0 | 3822 | 2.5535 | 0.9594 |
| 0.166 | 99.0 | 3861 | 2.5450 | 0.9592 |
| 0.1651 | 100.0 | 3900 | 2.5424 | 0.9609 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2