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whisper-NST2

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
hf-asr-leaderboard
NbAiLab/NST
Generated from Trainer
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metadata
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - automatic-speech-recognition
  - NbAiLab/NST
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-NST2
    results: []

whisper-NST2

This model is a fine-tuned version of openai/whisper-small on the NBAILAB/NST - NO-CLOSE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2990
  • Wer: 7.7537

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: 4e-05
  • train_batch_size: 96
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1846 0.1 1000 0.3460 14.9373
0.1325 0.2 2000 0.3413 11.4025
0.1135 0.3 3000 0.3428 12.6568
0.0955 0.4 4000 0.3140 10.7184
0.0871 0.5 5000 0.2907 9.4641
0.0774 0.6 6000 0.3019 11.4025
0.041 1.1 7000 0.2897 9.0080
0.0306 1.2 8000 0.3013 7.6397
0.0279 1.3 9000 0.2958 9.1220
0.0239 1.4 10000 0.2990 7.7537

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.6.1
  • Tokenizers 0.13.1