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Akashpb13
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Central_kurdish_xlsr

Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Central Kurdish
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results (legacy)
Model card Files
xet
 Community
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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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+ datasets:
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+ - mozilla-foundation/common_voice_8_0
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+
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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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+
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+ # Akashpb13/xlsr_hungarian_new
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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_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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+
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+ ## Model description
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+ "facebook/wav2vec2-xls-r-300m" was finetuned.
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+
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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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+
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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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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+
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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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+
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+
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+ ### Training results
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+
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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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+
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+
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+
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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 1.17.1.dev0
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+ - Tokenizers 0.10.3
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+
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+ #### Evaluation Commands
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+
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+ 1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
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+
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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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+