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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- en |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- librispeech_asr |
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- robust-speech-event |
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datasets: |
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- librispeech_asr |
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model-index: |
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- name: XLS-R-300M - English |
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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: LibriSpeech (clean) |
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type: librispeech_asr |
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config: clean |
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split: test |
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args: |
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language: en |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 12.29 |
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- name: Test CER |
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type: cer |
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value: 3.34 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: en |
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metrics: |
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- name: Validation WER |
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type: wer |
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value: 36.75 |
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- name: Validation CER |
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type: cer |
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value: 14.83 |
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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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config: en |
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split: test |
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args: |
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language: en |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 37.81 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: en |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 38.8 |
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--- |
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# |
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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 librispeech_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1444 |
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- Wer: 0.1167 |
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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: 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: 4 |
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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: 1000 |
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- num_epochs: 50 |
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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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| 2.9365 | 4.17 | 500 | 2.9398 | 0.9999 | |
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| 1.5444 | 8.33 | 1000 | 0.5947 | 0.4289 | |
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| 1.1367 | 12.5 | 1500 | 0.2751 | 0.2366 | |
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| 0.9972 | 16.66 | 2000 | 0.2032 | 0.1797 | |
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| 0.9118 | 20.83 | 2500 | 0.1786 | 0.1479 | |
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| 0.8664 | 24.99 | 3000 | 0.1641 | 0.1408 | |
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| 0.8251 | 29.17 | 3500 | 0.1537 | 0.1267 | |
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| 0.793 | 33.33 | 4000 | 0.1525 | 0.1244 | |
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| 0.785 | 37.5 | 4500 | 0.1470 | 0.1184 | |
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| 0.7612 | 41.66 | 5000 | 0.1446 | 0.1177 | |
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| 0.7478 | 45.83 | 5500 | 0.1449 | 0.1176 | |
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| 0.7443 | 49.99 | 6000 | 0.1444 | 0.1167 | |
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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 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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