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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- NbAiLab/NPSC |
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- generated_from_trainer |
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model-index: |
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- name: XLSR-1B-nynorsk-low |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: NPSC |
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type: NbAiLab/NPSC |
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args: 16K_mp3_nynorsk |
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metrics: |
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- name: Test (Nynorsk) WER |
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type: wer |
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value: 0.11319692134409612 |
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- name: Test (Nynorsk) CER |
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type: cer |
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value: 0.040263696587740365 |
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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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# XLSR-1B-nynorsk-low |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the NBAILAB/NPSC - 16K_MP3_NYNORSK dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2909 |
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- Wer: 0.1364 |
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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: 2e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- num_epochs: 60.0 |
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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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| 2.8979 | 1.0 | 500 | 2.9413 | 1.0 | |
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| 1.2224 | 2.0 | 1000 | 1.0359 | 0.7802 | |
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| 0.8643 | 3.01 | 1500 | 0.7746 | 0.5969 | |
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| 0.8211 | 4.01 | 2000 | 0.4882 | 0.3710 | |
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| 0.5287 | 5.01 | 2500 | 0.4060 | 0.3085 | |
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| 0.4724 | 6.01 | 3000 | 0.3297 | 0.2517 | |
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| 0.4357 | 7.01 | 3500 | 0.3106 | 0.2342 | |
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| 0.376 | 8.02 | 4000 | 0.2776 | 0.2072 | |
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| 0.3286 | 9.02 | 4500 | 0.2888 | 0.2032 | |
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| 0.3731 | 10.02 | 5000 | 0.2691 | 0.1835 | |
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| 0.306 | 11.02 | 5500 | 0.2536 | 0.1835 | |
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| 0.3025 | 12.02 | 6000 | 0.2758 | 0.1809 | |
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| 0.3413 | 13.03 | 6500 | 0.2791 | 0.1823 | |
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| 0.2601 | 14.03 | 7000 | 0.2912 | 0.1759 | |
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| 0.2332 | 15.03 | 7500 | 0.2582 | 0.1694 | |
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| 0.2108 | 16.03 | 8000 | 0.2717 | 0.1660 | |
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| 0.2122 | 17.03 | 8500 | 0.2848 | 0.1647 | |
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| 0.2369 | 18.04 | 9000 | 0.2548 | 0.1646 | |
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| 0.1906 | 19.04 | 9500 | 0.2667 | 0.1627 | |
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| 0.1943 | 20.04 | 10000 | 0.2662 | 0.1623 | |
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| 0.18 | 21.04 | 10500 | 0.2769 | 0.1561 | |
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| 0.1654 | 22.04 | 11000 | 0.2661 | 0.1558 | |
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| 0.1515 | 23.05 | 11500 | 0.2870 | 0.1597 | |
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| 0.147 | 24.05 | 12000 | 0.2778 | 0.1551 | |
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| 0.1622 | 25.05 | 12500 | 0.2753 | 0.1541 | |
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| 0.1522 | 26.05 | 13000 | 0.2932 | 0.1521 | |
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| 0.1522 | 27.05 | 13500 | 0.2548 | 0.1513 | |
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| 0.1319 | 28.06 | 14000 | 0.2811 | 0.1532 | |
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| 0.1261 | 29.06 | 14500 | 0.2786 | 0.1521 | |
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| 0.1391 | 30.06 | 15000 | 0.2651 | 0.1461 | |
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| 0.1486 | 31.06 | 15500 | 0.2866 | 0.1494 | |
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| 0.1121 | 32.06 | 16000 | 0.2641 | 0.1478 | |
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| 0.1114 | 33.07 | 16500 | 0.2910 | 0.1478 | |
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| 0.101 | 34.07 | 17000 | 0.2884 | 0.1443 | |
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| 0.1135 | 35.07 | 17500 | 0.3029 | 0.1469 | |
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| 0.0972 | 36.07 | 18000 | 0.2870 | 0.1467 | |
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| 0.1178 | 37.07 | 18500 | 0.2745 | 0.1450 | |
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| 0.0885 | 38.08 | 19000 | 0.2836 | 0.1440 | |
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| 0.1144 | 39.08 | 19500 | 0.2761 | 0.1446 | |
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| 0.0997 | 40.08 | 20000 | 0.2806 | 0.1439 | |
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| 0.1012 | 41.08 | 20500 | 0.2878 | 0.1413 | |
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| 0.0902 | 42.08 | 21000 | 0.2832 | 0.1452 | |
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| 0.0804 | 43.09 | 21500 | 0.2911 | 0.1458 | |
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| 0.0762 | 44.09 | 22000 | 0.2708 | 0.1441 | |
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| 0.0758 | 45.09 | 22500 | 0.2804 | 0.1434 | |
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| 0.0874 | 46.09 | 23000 | 0.2831 | 0.1407 | |
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| 0.0895 | 47.09 | 23500 | 0.2913 | 0.1396 | |
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| 0.0975 | 48.1 | 24000 | 0.2956 | 0.1411 | |
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| 0.0758 | 49.1 | 24500 | 0.2920 | 0.1385 | |
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| 0.0704 | 50.1 | 25000 | 0.2788 | 0.1383 | |
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| 0.0707 | 51.1 | 25500 | 0.2822 | 0.1388 | |
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| 0.0664 | 52.1 | 26000 | 0.2876 | 0.1371 | |
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| 0.0692 | 53.11 | 26500 | 0.2815 | 0.1377 | |
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| 0.0799 | 54.11 | 27000 | 0.2806 | 0.1363 | |
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| 0.0611 | 55.11 | 27500 | 0.2878 | 0.1363 | |
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| 0.0759 | 56.11 | 28000 | 0.2900 | 0.1365 | |
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| 0.0801 | 57.11 | 28500 | 0.2881 | 0.1375 | |
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| 0.0644 | 58.12 | 29000 | 0.2898 | 0.1362 | |
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| 0.068 | 59.12 | 29500 | 0.2913 | 0.1369 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.0 |
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