Total runs:
3.0K
Run Growth:
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Growth Rate:
34.05%
Sponsored by
APIMaster
sil-ai / w2v2-kaqchikel
Model's Last Updated: August 26 2022
automatic-speech-recognition
Introduction of w2v2-kaqchikel
Model Details of w2v2-kaqchikel
wav2vec2-large-xls-r-300m-kaqchikel-with-bloom
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on a collection of audio from Deditos videos in Kaqchikel provided by Viña Studios and Kaqchikel audio from audiobooks on Bloom Library . It achieves the following results on the evaluation set:
- Loss: 0.6700
- Cer: 0.0854
- Wer: 0.3069
Model description
- Homepage: SIL AI
- Point of Contact: SIL AI email
- Source Data: Bloom Library and Viña Studios
This model is a baseline model finetuned from XLS-R 300m . Users should refer to the original model for tutorials on using a trained model for inference.
Intended uses & limitations
Users of this model should abide by the UN Declarations on the Rights of Indigenous Peoples .
This model is released under the MIT license and no guarantees are made regarding the performance of the model is specific situations.
Training and evaluation data
Training, Validation, and Test datasets were generated from the same corpus, ensuring that no duplicate files were used.
Training procedure
Standard finetuning of XLS-R was used based on the examples in the Hugging Face Transformers Github
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 11.1557 | 1.84 | 100 | 4.2251 | 1.0 | 1.0 |
| 3.7231 | 3.7 | 200 | 3.5794 | 1.0 | 1.0 |
| 3.3076 | 5.55 | 300 | 3.4362 | 1.0 | 1.0 |
| 3.2495 | 7.4 | 400 | 3.2553 | 1.0 | 1.0 |
| 3.2076 | 9.26 | 500 | 3.2932 | 1.0 | 1.0 |
| 3.1304 | 11.11 | 600 | 3.1100 | 1.0 | 1.0 |
| 2.899 | 12.95 | 700 | 2.4021 | 0.8477 | 1.0 |
| 2.2875 | 14.81 | 800 | 1.5473 | 0.4790 | 0.9984 |
| 1.7605 | 16.66 | 900 | 1.1034 | 0.3061 | 0.9192 |
| 1.3802 | 18.51 | 1000 | 0.9422 | 0.2386 | 0.8530 |
| 1.0989 | 20.37 | 1100 | 0.7429 | 0.1667 | 0.6042 |
| 0.857 | 22.22 | 1200 | 0.7490 | 0.1499 | 0.5751 |
| 0.6899 | 24.07 | 1300 | 0.6376 | 0.1286 | 0.4798 |
| 0.5927 | 25.92 | 1400 | 0.6887 | 0.1232 | 0.4443 |
| 0.4699 | 27.77 | 1500 | 0.6341 | 0.1184 | 0.4378 |
| 0.4029 | 29.62 | 1600 | 0.6341 | 0.1103 | 0.4216 |
| 0.3492 | 31.48 | 1700 | 0.6709 | 0.1121 | 0.4120 |
| 0.3019 | 33.33 | 1800 | 0.7665 | 0.1097 | 0.4136 |
| 0.2681 | 35.18 | 1900 | 0.6671 | 0.1085 | 0.4120 |
| 0.2491 | 37.04 | 2000 | 0.7049 | 0.1010 | 0.3748 |
| 0.2108 | 38.88 | 2100 | 0.6699 | 0.1064 | 0.3974 |
| 0.2146 | 40.73 | 2200 | 0.7037 | 0.1046 | 0.3780 |
| 0.1854 | 42.59 | 2300 | 0.6970 | 0.1055 | 0.4006 |
| 0.1693 | 44.44 | 2400 | 0.6593 | 0.0980 | 0.3764 |
| 0.1628 | 46.29 | 2500 | 0.7162 | 0.0998 | 0.3764 |
| 0.156 | 48.15 | 2600 | 0.6445 | 0.0998 | 0.3829 |
| 0.1439 | 49.99 | 2700 | 0.6437 | 0.1004 | 0.3845 |
| 0.1292 | 51.84 | 2800 | 0.6471 | 0.0944 | 0.3457 |
| 0.1287 | 53.7 | 2900 | 0.6411 | 0.0923 | 0.3538 |
| 0.1186 | 55.55 | 3000 | 0.6754 | 0.0992 | 0.3813 |
| 0.1175 | 57.4 | 3100 | 0.6741 | 0.0953 | 0.3538 |
| 0.1082 | 59.26 | 3200 | 0.6949 | 0.0977 | 0.3619 |
| 0.105 | 61.11 | 3300 | 0.6919 | 0.0983 | 0.3683 |
| 0.1048 | 62.95 | 3400 | 0.6802 | 0.0950 | 0.3425 |
| 0.092 | 64.81 | 3500 | 0.6830 | 0.0962 | 0.3263 |
| 0.0904 | 66.66 | 3600 | 0.6993 | 0.0971 | 0.3554 |
| 0.0914 | 68.51 | 3700 | 0.6932 | 0.0995 | 0.3554 |
| 0.0823 | 70.37 | 3800 | 0.6742 | 0.0950 | 0.3409 |
| 0.0799 | 72.22 | 3900 | 0.6852 | 0.0917 | 0.3279 |
| 0.0767 | 74.07 | 4000 | 0.6684 | 0.0929 | 0.3489 |
| 0.0736 | 75.92 | 4100 | 0.6611 | 0.0923 | 0.3393 |
| 0.0708 | 77.77 | 4200 | 0.7123 | 0.0944 | 0.3393 |
| 0.0661 | 79.62 | 4300 | 0.6577 | 0.0899 | 0.3247 |
| 0.0651 | 81.48 | 4400 | 0.6671 | 0.0869 | 0.3150 |
| 0.0607 | 83.33 | 4500 | 0.6980 | 0.0893 | 0.3231 |
| 0.0552 | 85.18 | 4600 | 0.6947 | 0.0884 | 0.3183 |
| 0.0574 | 87.04 | 4700 | 0.6652 | 0.0899 | 0.3183 |
| 0.0503 | 88.88 | 4800 | 0.6798 | 0.0863 | 0.3053 |
| 0.0479 | 90.73 | 4900 | 0.6690 | 0.0884 | 0.3166 |
| 0.0483 | 92.59 | 5000 | 0.6789 | 0.0872 | 0.3069 |
| 0.0437 | 94.44 | 5100 | 0.6758 | 0.0875 | 0.3069 |
| 0.0458 | 96.29 | 5200 | 0.6662 | 0.0884 | 0.3102 |
| 0.0434 | 98.15 | 5300 | 0.6699 | 0.0881 | 0.3069 |
| 0.0449 | 99.99 | 5400 | 0.6700 | 0.0854 | 0.3069 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 2.2.1
- Tokenizers 0.10.3
Runs of sil-ai w2v2-kaqchikel on huggingface.co
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More Information About w2v2-kaqchikel huggingface.co Model
Url of w2v2-kaqchikel
w2v2-kaqchikel huggingface.co Url
Provider of w2v2-kaqchikel huggingface.co
Other API from sil-ai
Updated:October 21 2022
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