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whisper-large-no-is-145h-30k-steps

Automatic Speech Recognition
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whisper
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metadata
license: apache-2.0
base_model: NbAiLab/nb-whisper-large
tags:
  - generated_from_trainer
datasets:
  - samromur_asr
metrics:
  - wer
model-index:
  - name: whisper-large-no-is-145h-30k-steps
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: samromur_asr
          type: samromur_asr
          config: samromur_asr
          split: test
          args: samromur_asr
        metrics:
          - name: Wer
            type: wer
            value: 8.020304568527918

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whisper-large-no-is-145h-30k-steps

This model is a fine-tuned version of NbAiLab/nb-whisper-large on the samromur_asr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1280
  • Wer: 8.0203

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • 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: 30000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3237 0.1778 1000 0.3331 24.9280
0.2334 0.3556 2000 0.2369 19.2033
0.1932 0.5333 3000 0.2121 16.7584
0.1681 0.7111 4000 0.1874 14.9669
0.1487 0.8889 5000 0.1720 13.8274
0.0911 1.0667 6000 0.1644 13.2541
0.0765 1.2444 7000 0.1577 12.3332
0.0843 1.4222 8000 0.1469 11.8722
0.0797 1.6 9000 0.1437 11.3156
0.0778 1.7778 10000 0.1365 10.9298
0.0789 1.9556 11000 0.1329 10.7554
0.039 2.1333 12000 0.1353 10.3625
0.0394 2.3111 13000 0.1399 10.2872
0.0438 2.4889 14000 0.1357 10.0926
0.0365 2.6667 15000 0.1287 9.8632
0.0406 2.8444 16000 0.1266 9.6435
0.0193 3.0222 17000 0.1284 9.3258
0.0181 3.2 18000 0.1309 9.3019
0.0215 3.3778 19000 0.1317 9.1299
0.0207 3.5556 20000 0.1287 8.8767
0.0185 3.7333 21000 0.1285 8.8731
0.0162 3.9111 22000 0.1272 8.6581
0.007 4.0889 23000 0.1285 8.6175
0.0076 4.2667 24000 0.1296 8.3655
0.0074 4.4444 25000 0.1277 8.4037
0.0076 4.6222 26000 0.1289 8.3464
0.006 4.8 27000 0.1257 8.1756
0.0067 4.9778 28000 0.1252 8.0979
0.0025 5.1556 29000 0.1269 8.0322
0.0032 5.3333 30000 0.1280 8.0203

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1