poonehmousavi
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Upload hyperparams.yaml
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hyperparams.yaml
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# ################################
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# Model: Whisper (Encoder-Decoder) + NLL
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# Augmentation: TimeDomainSpecAugment
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# Authors: Pooneh Mousavi 2022
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# ################################
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# URL for the biggest Fairseq english whisper model.
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whisper_hub: openai/whisper-large-v2
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# Normalize inputs with
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# the same normalization done in the paper. Refer to Appendix C for further information.
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normalized_transcripts: True
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language: french
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auto_mix_prec: False
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sample_rate: 16000
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# These values are only used for the searchers.
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# They needs to be hardcoded and should not be changed with Whisper.
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# They are used as part of the searching process.
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# The bos token of the searcher will be timestamp_index
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# and will be concatenated with the bos, language and task tokens.
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timestamp_index: 50363
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eos_index: 50257
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bos_index: 50258
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# Decoding parameters
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min_decode_ratio: 0.0
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max_decode_ratio: 0.1
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test_beam_size: 8
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# Model parameters
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freeze_whisper: True
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freeze_encoder: True
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whisper: !new:speechbrain.lobes.models.huggingface_whisper.HuggingFaceWhisper
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source: !ref <whisper_hub>
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freeze: !ref <freeze_whisper>
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freeze_encoder: !ref <freeze_encoder>
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save_path: whisper_checkpoints
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encoder_only: False
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decoder: !new:speechbrain.decoders.seq2seq.S2SWhisperGreedySearch
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model: !ref <whisper>
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bos_index: !ref <timestamp_index>
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eos_index: !ref <eos_index>
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min_decode_ratio: !ref <min_decode_ratio>
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max_decode_ratio: !ref <max_decode_ratio>
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# test_beam_searcher: !new:speechbrain.decoders.seq2seq.S2SWhisperBeamSearch
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# module: [!ref <whisper>]
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# bos_index: !ref <timestamp_index>
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# eos_index: !ref <eos_index>
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# min_decode_ratio: !ref <min_decode_ratio>
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# max_decode_ratio: !ref <max_decode_ratio>
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# beam_size: !ref <test_beam_size>
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modules:
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whisper: !ref <whisper>
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decoder: !ref <decoder>
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
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loadables:
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whisper: !ref <whisper>
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