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--- |
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language: |
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- bas |
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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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- bas |
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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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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-bas-v1 |
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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: bas |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.3566497929130234 |
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- name: Test CER |
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type: cer |
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value: 0.1102657634184471 |
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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: bas |
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metrics: |
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- name: Test WER |
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type: wer |
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value: NA |
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- name: Test CER |
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type: cer |
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value: NA |
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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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# wav2vec2-large-xls-r-300m-bas-v1 |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BAS dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5997 |
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- Wer: 0.3870 |
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### Evaluation Commands |
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1. To evaluate on mozilla-foundation/common_voice_8_0 with test split |
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python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1 --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs |
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2. To evaluate on speech-recognition-community-v2/dev_data |
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Basaa (bas) language isn't available in speech-recognition-community-v2/dev_data |
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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: 500 |
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- num_epochs: 100 |
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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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| 12.7076 | 5.26 | 200 | 3.6361 | 1.0 | |
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| 3.1657 | 10.52 | 400 | 3.0101 | 1.0 | |
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| 2.3987 | 15.78 | 600 | 0.9125 | 0.6774 | |
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| 1.0079 | 21.05 | 800 | 0.6477 | 0.5352 | |
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| 0.7392 | 26.31 | 1000 | 0.5432 | 0.4929 | |
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| 0.6114 | 31.57 | 1200 | 0.5498 | 0.4639 | |
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| 0.5222 | 36.83 | 1400 | 0.5220 | 0.4561 | |
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| 0.4648 | 42.1 | 1600 | 0.5586 | 0.4289 | |
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| 0.4103 | 47.36 | 1800 | 0.5337 | 0.4082 | |
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| 0.3692 | 52.62 | 2000 | 0.5421 | 0.3861 | |
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| 0.3403 | 57.88 | 2200 | 0.5549 | 0.4096 | |
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| 0.3011 | 63.16 | 2400 | 0.5833 | 0.3925 | |
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| 0.2932 | 68.42 | 2600 | 0.5674 | 0.3815 | |
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| 0.2696 | 73.68 | 2800 | 0.5734 | 0.3889 | |
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| 0.2496 | 78.94 | 3000 | 0.5968 | 0.3985 | |
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| 0.2289 | 84.21 | 3200 | 0.5888 | 0.3893 | |
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| 0.2091 | 89.47 | 3400 | 0.5849 | 0.3852 | |
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| 0.2005 | 94.73 | 3600 | 0.5938 | 0.3875 | |
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| 0.1876 | 99.99 | 3800 | 0.5997 | 0.3870 | |
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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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