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--- |
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language: |
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- mn |
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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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- robust-speech-event |
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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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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-mn |
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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: mn |
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metrics: |
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- name: Test WER using LM |
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type: wer |
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value: 31.3919 |
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- name: Test CER using LM |
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type: cer |
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value: 10.2565 |
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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: mn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 65.26 |
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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: mn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 63.09 |
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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-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5502 |
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- Wer: 0.4042 |
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## Training and evaluation data |
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Evaluation is conducted in Notebook, you can see within the repo "notebook_evaluation_wav2vec2_mn.ipynb" |
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Test WER without LM |
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wer = 58.2171 % |
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cer = 16.0670 % |
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Test WER using |
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wer = 31.3919 % |
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cer = 10.2565 % |
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How to use eval.py |
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``` |
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huggingface-cli login #login to huggingface for getting auth token to access the common voice v8 |
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#running with LM |
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python eval.py --model_id ayameRushia/wav2vec2-large-xls-r-300m-mn --dataset mozilla-foundation/common_voice_8_0 --config mn --split test |
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# running without LM |
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python eval.py --model_id ayameRushia/wav2vec2-large-xls-r-300m-mn --dataset mozilla-foundation/common_voice_8_0 --config mn --split test --greedy |
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``` |
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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: 0.0003 |
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- train_batch_size: 32 |
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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: 64 |
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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: 40.0 |
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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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| No log | 6.35 | 400 | 0.9380 | 0.7902 | |
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| 3.2674 | 12.7 | 800 | 0.5794 | 0.5309 | |
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| 0.7531 | 19.05 | 1200 | 0.5749 | 0.4815 | |
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| 0.5382 | 25.4 | 1600 | 0.5530 | 0.4447 | |
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| 0.4293 | 31.75 | 2000 | 0.5709 | 0.4237 | |
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| 0.4293 | 38.1 | 2400 | 0.5476 | 0.4059 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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