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metadata
language:
  - bn
license: apache-2.0
tags:
  - automatic-speech-recognition
  - bn
  - hf-asr-leaderboard
  - openslr_SLR53
  - robust-speech-event
datasets:
  - openslr
  - SLR53
  - AI4Bharat/IndicCorp
metrics:
  - wer
  - cer
model-index:
  - name: arijitx/wav2vec2-xls-r-300m-bengali
    results:
      - task:
          type: automatic-speech-recognition
          name: Speech Recognition
        dataset:
          type: openslr
          name: Open SLR
          args: SLR53
        metrics:
          - type: wer
            value: 0.21726385291857586
            name: Test WER
          - type: cer
            value: 0.04725010353701041
            name: Test CER
          - type: wer
            value: 0.15322879016421437
            name: Test WER with lm
          - type: cer
            value: 0.03413696666806267
            name: Test CER with lm

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the OPENSLR_SLR53 - bengali dataset. It achieves the following results on the evaluation set.

Without language model :

  • WER: 0.21726385291857586
  • CER: 0.04725010353701041

With 5 gram language model trained on 30M sentences randomly chosen from AI4Bharat IndicCorp dataset :

  • WER: 0.15322879016421437
  • CER: 0.03413696666806267

Note : 5% of a total 10935 samples have been used for evaluation. Evaluation set has 10935 examples which was not part of training training was done on first 95% and eval was done on last 5%. Training was stopped after 180k steps. Output predictions are available under files section.

Training hyperparameters

The following hyperparameters were used during training:

  • dataset_name="openslr"
  • model_name_or_path="facebook/wav2vec2-xls-r-300m"
  • dataset_config_name="SLR53"
  • output_dir="./wav2vec2-xls-r-300m-bengali"
  • overwrite_output_dir
  • num_train_epochs="50"
  • per_device_train_batch_size="32"
  • per_device_eval_batch_size="32"
  • gradient_accumulation_steps="1"
  • learning_rate="7.5e-5"
  • warmup_steps="2000"
  • length_column_name="input_length"
  • evaluation_strategy="steps"
  • text_column_name="sentence"
  • chars_to_ignore , ? . ! - ; : " “ % ‘ ” � — ’ … –
  • save_steps="2000"
  • eval_steps="3000"
  • logging_steps="100"
  • 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"
  • preprocessing_num_workers 32

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0

Notes