whisper-tiny-cv-full-synthetic-pt

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5305

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: 5e-05
  • train_batch_size: 256
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 10

Training results

Training Loss Epoch Step Validation Loss
0.6982 0.2907 50 0.6187
0.5012 0.5814 100 0.5461
0.448 0.8721 150 0.5133
0.3321 1.1628 200 0.4977
0.3198 1.4535 250 0.4814
0.3069 1.7442 300 0.4700
0.2712 2.0349 350 0.4582
0.1954 2.3256 400 0.4599
0.2032 2.6163 450 0.4585
0.2011 2.9070 500 0.4517
0.1334 3.1977 550 0.4576
0.1309 3.4884 600 0.4596
0.13 3.7791 650 0.4613
0.1146 4.0698 700 0.4667
0.0906 4.3605 750 0.4702
0.0918 4.6512 800 0.4754
0.0955 4.9419 850 0.4741
0.0599 5.2326 900 0.4841
0.0647 5.5233 950 0.4877
0.0611 5.8140 1000 0.4953
0.0505 6.1047 1050 0.5025
0.042 6.3953 1100 0.5023
0.0448 6.6860 1150 0.5082
0.0452 6.9767 1200 0.5040
0.0294 7.2674 1250 0.5132
0.032 7.5581 1300 0.5164
0.0309 7.8488 1350 0.5183
0.0239 8.1395 1400 0.5241
0.0232 8.4302 1450 0.5250
0.0244 8.7209 1500 0.5256
0.024 9.0116 1550 0.5278
0.0207 9.3023 1600 0.5291
0.0217 9.5930 1650 0.5303
0.0203 9.8837 1700 0.5305

Framework versions

  • Transformers 4.50.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2
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