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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- automatic-speech-recognition |
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- sudoping01/dataset-bo |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: bomu-asr |
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results: [] |
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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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# bomu-asr |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the SUDOPING01/DATASET-BO - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1682 |
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- Wer: 0.1458 |
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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: 0.0005 |
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- train_batch_size: 12 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 24 |
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- total_eval_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: 500 |
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- num_epochs: 15.0 |
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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 | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 3.4285 | 0.3356 | 100 | 3.4152 | 1.0 | |
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| 2.6743 | 0.6711 | 200 | 2.5978 | 0.9967 | |
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| 0.4489 | 1.0067 | 300 | 0.3998 | 0.4768 | |
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| 0.3195 | 1.3423 | 400 | 0.2667 | 0.3600 | |
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| 0.2897 | 1.6779 | 500 | 0.2343 | 0.3141 | |
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| 0.2234 | 2.0134 | 600 | 0.1843 | 0.2586 | |
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| 0.2174 | 2.3490 | 700 | 0.1698 | 0.2443 | |
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| 0.2425 | 2.6846 | 800 | 0.1626 | 0.2267 | |
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| 0.1674 | 3.0201 | 900 | 0.1450 | 0.2111 | |
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| 0.1351 | 3.3557 | 1000 | 0.1464 | 0.2070 | |
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| 0.1522 | 3.6913 | 1100 | 0.1405 | 0.2016 | |
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| 0.1385 | 4.0268 | 1200 | 0.1359 | 0.1903 | |
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| 0.1309 | 4.3624 | 1300 | 0.1349 | 0.1941 | |
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| 0.1358 | 4.6980 | 1400 | 0.1290 | 0.1837 | |
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| 0.0982 | 5.0336 | 1500 | 0.1240 | 0.1745 | |
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| 0.0923 | 5.3691 | 1600 | 0.1256 | 0.1786 | |
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| 0.1429 | 5.7047 | 1700 | 0.1235 | 0.1747 | |
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| 0.0903 | 6.0403 | 1800 | 0.1289 | 0.1718 | |
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| 0.0859 | 6.3758 | 1900 | 0.1205 | 0.1757 | |
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| 0.065 | 6.7114 | 2000 | 0.1188 | 0.1710 | |
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| 0.0834 | 7.0470 | 2100 | 0.1300 | 0.1708 | |
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| 0.0701 | 7.3826 | 2200 | 0.1258 | 0.1723 | |
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| 0.0682 | 7.7181 | 2300 | 0.1281 | 0.1648 | |
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| 0.0555 | 8.0537 | 2400 | 0.1237 | 0.1604 | |
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| 0.0662 | 8.3893 | 2500 | 0.1262 | 0.1588 | |
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| 0.0632 | 8.7248 | 2600 | 0.1291 | 0.1626 | |
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| 0.0448 | 9.0604 | 2700 | 0.1347 | 0.1620 | |
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| 0.0522 | 9.3960 | 2800 | 0.1351 | 0.1610 | |
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| 0.0552 | 9.7315 | 2900 | 0.1353 | 0.1604 | |
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| 0.0325 | 10.0671 | 3000 | 0.1470 | 0.1573 | |
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| 0.0378 | 10.4027 | 3100 | 0.1413 | 0.1581 | |
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| 0.0271 | 10.7383 | 3200 | 0.1469 | 0.1556 | |
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| 0.0434 | 11.0738 | 3300 | 0.1530 | 0.1559 | |
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| 0.0352 | 11.4094 | 3400 | 0.1546 | 0.1537 | |
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| 0.052 | 11.7450 | 3500 | 0.1512 | 0.1560 | |
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| 0.0803 | 12.0805 | 3600 | 0.1584 | 0.1523 | |
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| 0.0425 | 12.4161 | 3700 | 0.1588 | 0.1505 | |
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| 0.0327 | 12.7517 | 3800 | 0.1633 | 0.1507 | |
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| 0.0444 | 13.0872 | 3900 | 0.1660 | 0.1509 | |
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| 0.0275 | 13.4228 | 4000 | 0.1650 | 0.1481 | |
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| 0.0358 | 13.7584 | 4100 | 0.1616 | 0.1471 | |
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| 0.0338 | 14.0940 | 4200 | 0.1656 | 0.1466 | |
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| 0.0304 | 14.4295 | 4300 | 0.1653 | 0.1455 | |
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| 0.0268 | 14.7651 | 4400 | 0.1684 | 0.1456 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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