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whisper-small-lg-CV-v4

Automatic Speech Recognition
Transformers
Safetensors
whisper
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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-small-lg-CV-v4
    results: []

whisper-small-lg-CV-v4

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4866
  • Wer: 0.1829
  • Cer: 0.0436

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 80
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.545 1.0 4442 0.5612 0.8131 0.3503
0.4678 2.0 8884 0.3652 0.8879 0.3107
0.3088 3.0 13326 0.3027 0.5332 0.1688
0.2227 4.0 17768 0.2697 0.5612 0.2191
0.1615 5.0 22210 0.2638 0.2890 0.0834
0.1138 6.0 26652 0.2823 0.3445 0.1247
0.0783 7.0 31094 0.2914 0.2683 0.0754
0.0554 8.0 35536 0.3115 0.2488 0.0658
0.0396 9.0 39978 0.3147 0.2329 0.0524
0.0279 10.0 44420 0.3267 0.2213 0.0499
0.0207 11.0 48862 0.3438 0.2167 0.0494
0.0167 12.0 53304 0.3460 0.2090 0.0449
0.0138 13.0 57746 0.3553 0.2043 0.0447
0.0118 14.0 62188 0.3806 0.2167 0.0486
0.0101 15.0 66630 0.3755 0.2066 0.0463
0.0089 16.0 71072 0.3849 0.2045 0.0450
0.0079 17.0 75514 0.3918 0.1974 0.0447
0.0071 18.0 79956 0.3998 0.1968 0.0435
0.0064 19.0 84398 0.4117 0.2016 0.0442
0.0059 20.0 88840 0.4077 0.1985 0.0443
0.0052 21.0 93282 0.4198 0.1976 0.0434
0.005 22.0 97724 0.4248 0.1964 0.0427
0.0044 23.0 102166 0.4303 0.1964 0.0445
0.0038 24.0 106608 0.4429 0.1970 0.0439
0.0036 25.0 111050 0.4448 0.2014 0.0463
0.0035 26.0 115492 0.4585 0.1952 0.0435
0.003 27.0 119934 0.4450 0.1836 0.0404
0.003 28.0 124376 0.4620 0.1869 0.0409
0.0028 29.0 128818 0.4665 0.1885 0.0401
0.0026 30.0 133260 0.4837 0.1937 0.0440
0.0024 31.0 137702 0.4758 0.1850 0.0399
0.0023 32.0 142144 0.4879 0.1891 0.0418
0.0021 33.0 146586 0.4674 0.1883 0.0414
0.0019 34.0 151028 0.4782 0.1852 0.0413
0.0018 35.0 155470 0.4834 0.1840 0.0411
0.0016 36.0 159912 0.4990 0.1912 0.0428
0.0017 37.0 164354 0.4866 0.1829 0.0436

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.1.0+cu118
  • Datasets 3.1.0
  • Tokenizers 0.21.0