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--- |
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language: |
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- ckb |
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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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- ckb |
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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: Akashpb13/Central_kurdish_xlsr |
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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: ckb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.36754389884276845 |
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- name: Test CER |
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type: cer |
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value: 0.07827896768334217 |
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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: ckb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.36754389884276845 |
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- name: Test CER |
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type: cer |
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value: 0.07827896768334217 |
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--- |
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# Akashpb13/Central_kurdish_xlsr |
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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_7_0 - hu dataset. |
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It achieves the following results on evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other and dev datasets): |
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- Loss: 0.348580 |
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- Wer: 0.401147 |
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## Model description |
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"facebook/wav2vec2-xls-r-300m" was finetuned. |
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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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Training data - |
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Common voice Central Kurdish train.tsv, dev.tsv, invalidated.tsv, reported.tsv, and other.tsv |
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Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0 |
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## Training procedure |
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For creating the train dataset, all possible datasets were appended and 90-10 split was used. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.000095637994662983496 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 13 |
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- gradient_accumulation_steps: 2 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 200 |
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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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| Step | Training Loss | Validation Loss | Wer | |
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|-------|---------------|-----------------|----------| |
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| 500 | 5.097800 | 2.190326 | 1.001207 | |
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| 1000 | 0.797500 | 0.331392 | 0.576819 | |
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| 1500 | 0.405100 | 0.262009 | 0.549049 | |
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| 2000 | 0.322100 | 0.248178 | 0.479626 | |
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| 2500 | 0.264600 | 0.258866 | 0.488983 | |
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| 3000 | 0.228300 | 0.261523 | 0.469665 | |
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| 3500 | 0.201000 | 0.270135 | 0.451856 | |
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| 4000 | 0.180900 | 0.279302 | 0.448536 | |
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| 4500 | 0.163800 | 0.280921 | 0.459704 | |
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| 5000 | 0.147300 | 0.319249 | 0.471778 | |
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| 5500 | 0.137600 | 0.289546 | 0.449140 | |
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| 6000 | 0.132000 | 0.311350 | 0.458195 | |
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| 6500 | 0.117100 | 0.316726 | 0.432840 | |
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| 7000 | 0.109200 | 0.302210 | 0.439481 | |
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| 7500 | 0.104900 | 0.325913 | 0.439481 | |
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| 8000 | 0.097500 | 0.329446 | 0.431935 | |
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| 8500 | 0.088600 | 0.345259 | 0.425898 | |
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| 9000 | 0.084900 | 0.342891 | 0.428313 | |
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| 9500 | 0.080900 | 0.353081 | 0.424389 | |
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| 10000 | 0.075600 | 0.347063 | 0.424992 | |
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| 10500 | 0.072800 | 0.330086 | 0.424691 | |
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| 11000 | 0.068100 | 0.350658 | 0.421974 | |
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| 11500 | 0.064700 | 0.342949 | 0.413522 | |
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| 12000 | 0.061500 | 0.341704 | 0.415334 | |
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| 12500 | 0.059500 | 0.346279 | 0.411410 | |
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| 13000 | 0.057400 | 0.349901 | 0.407184 | |
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| 13500 | 0.056400 | 0.347733 | 0.402656 | |
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| 14000 | 0.053300 | 0.344899 | 0.405976 | |
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| 14500 | 0.052900 | 0.346708 | 0.402656 | |
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| 15000 | 0.050600 | 0.344118 | 0.400845 | |
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| 15500 | 0.050200 | 0.348396 | 0.402958 | |
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| 16000 | 0.049800 | 0.348312 | 0.401751 | |
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| 16500 | 0.051900 | 0.348372 | 0.401147 | |
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| 17000 | 0.049800 | 0.348580 | 0.401147 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 1.18.1 |
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- Tokenizers 0.10.3 |
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#### Evaluation Commands |
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1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test` |
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```bash |
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python eval.py --model_id Akashpb13/Central_kurdish_xlsr --dataset mozilla-foundation/common_voice_8_0 --config ckb --split test |
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``` |
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