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whisper-NST-cons2e5

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-NST-cons2e5
    results: []

whisper-NST-cons2e5

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: 0.3521
  • Wer: 11.8586

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: 2e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2517 0.1 1000 0.4131 18.4721
0.1931 0.2 2000 0.3531 19.0422
0.1598 0.3 3000 0.3605 16.8757
0.1541 0.4 4000 0.3367 14.4812
0.1443 0.5 5000 0.3274 13.3409
0.1301 0.6 6000 0.3481 10.7184
0.1266 0.7 7000 0.3452 12.9989
0.1216 0.8 8000 0.3215 10.8324
0.1121 0.9 9000 0.3160 11.5165
0.1171 1.0 10000 0.3521 11.8586

Framework versions

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