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--- |
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language: |
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- ur |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- ur |
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- robust-speech-event |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: '' |
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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: Common Voice 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: ur |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 44.13 |
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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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# |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9613 |
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- Wer: 0.5376 |
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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: 7.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 50 |
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- num_epochs: 50.0 |
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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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| 5.3118 | 1.96 | 100 | 2.9093 | 0.9982 | |
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| 2.2071 | 3.92 | 200 | 1.1737 | 0.7779 | |
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| 1.6098 | 5.88 | 300 | 0.9984 | 0.7015 | |
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| 1.4333 | 7.84 | 400 | 0.9800 | 0.6705 | |
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| 1.2859 | 9.8 | 500 | 0.9582 | 0.6487 | |
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| 1.2073 | 11.76 | 600 | 0.8841 | 0.6077 | |
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| 1.1417 | 13.73 | 700 | 0.9118 | 0.6343 | |
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| 1.0988 | 15.69 | 800 | 0.9217 | 0.6196 | |
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| 1.0279 | 17.65 | 900 | 0.9165 | 0.5867 | |
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| 0.9765 | 19.61 | 1000 | 0.9306 | 0.5978 | |
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| 0.9161 | 21.57 | 1100 | 0.9305 | 0.5768 | |
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| 0.8395 | 23.53 | 1200 | 0.9828 | 0.5819 | |
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| 0.8306 | 25.49 | 1300 | 0.9397 | 0.5760 | |
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| 0.7819 | 27.45 | 1400 | 0.9544 | 0.5742 | |
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| 0.7509 | 29.41 | 1500 | 0.9278 | 0.5690 | |
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| 0.7218 | 31.37 | 1600 | 0.9003 | 0.5587 | |
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| 0.6725 | 33.33 | 1700 | 0.9659 | 0.5554 | |
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| 0.6287 | 35.29 | 1800 | 0.9522 | 0.5561 | |
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| 0.6077 | 37.25 | 1900 | 0.9154 | 0.5465 | |
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| 0.5873 | 39.22 | 2000 | 0.9331 | 0.5469 | |
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| 0.5621 | 41.18 | 2100 | 0.9335 | 0.5491 | |
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| 0.5168 | 43.14 | 2200 | 0.9632 | 0.5458 | |
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| 0.5114 | 45.1 | 2300 | 0.9349 | 0.5387 | |
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| 0.4986 | 47.06 | 2400 | 0.9364 | 0.5380 | |
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| 0.4761 | 49.02 | 2500 | 0.9584 | 0.5391 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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