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--- |
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language: |
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- hy |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- hy |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-xls-r-1b-hy-cv |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_8_0 |
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name: Common Voice hy-AM |
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args: hy-AM |
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metrics: |
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- type: wer |
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value: 10.811865729898516 |
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name: WER LM |
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- type: cer |
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value: 2.2205361659079412 |
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name: CER LM |
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- task: |
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name: 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: hy |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 18.219363037089988 |
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- name: Test CER |
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type: cer |
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value: 7.075988867335752 |
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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 /WORKSPACE/DATA/HY/NOIZY_STUDENT_4/ - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1693 |
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- Wer: 0.2373 |
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- Cer: 0.0429 |
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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: 16 |
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- eval_batch_size: 64 |
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- seed: 842 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 5000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 1.255 | 7.24 | 500 | 0.2978 | 0.4294 | 0.0758 | |
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| 1.0058 | 14.49 | 1000 | 0.1883 | 0.2838 | 0.0483 | |
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| 0.9371 | 21.73 | 1500 | 0.1813 | 0.2627 | 0.0457 | |
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| 0.8999 | 28.98 | 2000 | 0.1693 | 0.2373 | 0.0429 | |
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| 0.8814 | 36.23 | 2500 | 0.1760 | 0.2420 | 0.0435 | |
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| 0.8364 | 43.47 | 3000 | 0.1765 | 0.2416 | 0.0419 | |
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| 0.8019 | 50.72 | 3500 | 0.1758 | 0.2311 | 0.0398 | |
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| 0.7665 | 57.96 | 4000 | 0.1745 | 0.2240 | 0.0399 | |
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| 0.7376 | 65.22 | 4500 | 0.1717 | 0.2190 | 0.0385 | |
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| 0.716 | 72.46 | 5000 | 0.1700 | 0.2147 | 0.0382 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2 |
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- Datasets 1.18.4.dev0 |
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- Tokenizers 0.11.0 |
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