Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Uyghur
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use lucio/xls-r-uyghur-cv8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucio/xls-r-uyghur-cv8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lucio/xls-r-uyghur-cv8")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lucio/xls-r-uyghur-cv8") model = AutoModelForCTC.from_pretrained("lucio/xls-r-uyghur-cv8") - Notebooks
- Google Colab
- Kaggle
| python xls-r-uyghur-cv8/run_speech_recognition_ctc.py \ | |
| --dataset_name="mozilla-foundation/common_voice_8_0" \ | |
| --model_name_or_path="facebook/wav2vec2-xls-r-300m" \ | |
| --dataset_config_name="ug" \ | |
| --train_split_name="train+validation" \ | |
| --eval_split_name="test" \ | |
| --output_dir="./xls-r-uyghur-cv8" \ | |
| --overwrite_output_dir \ | |
| --num_train_epochs="100" \ | |
| --per_device_train_batch_size="16" \ | |
| --per_device_eval_batch_size="8" \ | |
| --gradient_accumulation_steps="4" \ | |
| --learning_rate="1e-4" \ | |
| --warmup_steps="2000" \ | |
| --length_column_name="input_length" \ | |
| --evaluation_strategy="steps" \ | |
| --text_column_name="sentence" \ | |
| --chars_to_ignore , ? . ! \- \; \: \\ _ \| ‒ ☺ ♂ © « ¬ » \" „ “ % ” � — ’ ، ؛ ؟ ‹ › − … – \ | |
| --eval_metrics="wer" \ | |
| --save_steps="500" \ | |
| --eval_steps="500" \ | |
| --logging_steps="100" \ | |
| --min_duration_in_seconds="0.2" \ | |
| --layerdrop="0.0" \ | |
| --activation_dropout="0.1" \ | |
| --save_total_limit="3" \ | |
| --freeze_feature_encoder \ | |
| --feat_proj_dropout="0.0" \ | |
| --mask_time_prob="0.75" \ | |
| --mask_time_length="10" \ | |
| --mask_feature_prob="0.25" \ | |
| --mask_feature_length="64" \ | |
| --gradient_checkpointing \ | |
| --use_auth_token \ | |
| --fp16 \ | |
| --group_by_length \ | |
| --do_train --do_eval \ | |
| --push_to_hub | |