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--- |
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language: |
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- as |
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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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- as |
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- robust-speech-event |
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- model_for_talk |
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- hf-asr-leaderboard |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-as-with-LM-v2 |
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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 |
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type: mozilla-foundation/common_voice_8_0 |
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args: hsb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: [] |
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- name: Test CER |
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type: cer |
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value: [] |
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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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### Note: Files are missing. Probably, didn't get (git)pushed properly. :( |
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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 common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1679 |
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- Wer: 0.5761 |
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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: 0.000111 |
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- train_batch_size: 16 |
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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: 32 |
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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: 300 |
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- num_epochs: 200 |
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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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| 8.3852 | 10.51 | 200 | 3.6402 | 1.0 | |
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| 3.5374 | 21.05 | 400 | 3.3894 | 1.0 | |
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| 2.8645 | 31.56 | 600 | 1.3143 | 0.8303 | |
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| 1.1784 | 42.1 | 800 | 0.9417 | 0.6661 | |
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| 0.7805 | 52.62 | 1000 | 0.9292 | 0.6237 | |
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| 0.5973 | 63.15 | 1200 | 0.9489 | 0.6014 | |
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| 0.4784 | 73.67 | 1400 | 0.9916 | 0.5962 | |
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| 0.4138 | 84.21 | 1600 | 1.0272 | 0.6121 | |
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| 0.3491 | 94.72 | 1800 | 1.0412 | 0.5984 | |
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| 0.3062 | 105.26 | 2000 | 1.0769 | 0.6005 | |
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| 0.2707 | 115.77 | 2200 | 1.0708 | 0.5752 | |
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| 0.2459 | 126.31 | 2400 | 1.1285 | 0.6009 | |
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| 0.2234 | 136.82 | 2600 | 1.1209 | 0.5949 | |
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| 0.2035 | 147.36 | 2800 | 1.1348 | 0.5842 | |
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| 0.1876 | 157.87 | 3000 | 1.1480 | 0.5872 | |
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| 0.1669 | 168.41 | 3200 | 1.1496 | 0.5838 | |
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| 0.1595 | 178.92 | 3400 | 1.1721 | 0.5778 | |
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| 0.1505 | 189.46 | 3600 | 1.1654 | 0.5744 | |
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| 0.1486 | 199.97 | 3800 | 1.1679 | 0.5761 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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