README.md

metadata

language:
  - 'no'
license: apache-2.0
base_model: NbAiLabBeta/nb-whisper-large
tags:
  - audio
  - asr
  - automatic-speech-recognition
  - hf-asr-leaderboard
model-index:
  - name: nb-whisper-large-v0.8-vad3-verbatim
    results: []

nb-whisper-large-v0.8-vad3-verbatim

This model is a fine-tuned version of NbAiLabBeta/nb-whisper-large on the NbAiLab/NPSC dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 7e-05
• lr_scheduler_type: linear
• per_device_train_batch_size: 8
• total_train_batch_size_per_node: 32
• total_train_batch_size: 1024
• total_optimization_steps: 250
• starting_optimization_step: None
• finishing_optimization_step: 250
• num_train_dataset_workers: 32
• num_hosts: 32
• total_num_training_examples: 256,000
• steps_per_epoch: To be computed after first epoch
• num_beams: None
• weight_decay: 0.01
• adam_beta1: 0.9
• adam_beta2: 0.98
• adam_epsilon: 1e-06
• dropout: True
• bpe_dropout_probability: 0.2
• activation_dropout_probability: 0.1

Training results

step	validation_loss	train_loss	validation_wer	validation_cer	validation_exact_wer	validation_exact_cer
0	1.2831	1.1864	18.9083	11.8409	33.9801	15.0322

Framework versions

• Transformers 4.36.2
• Datasets 2.16.1
• Tokenizers 0.15.0