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whisper-synthesized-turkish-8-hour

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: 0.2300
  • Wer: 23.0527

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.2682 0.52 100 0.5845 99.7901
0.4591 1.04 200 0.3895 21.4541
0.2482 1.56 300 0.2241 12.2145
0.1554 2.08 400 0.2092 11.7825
0.096 2.6 500 0.2035 13.9057
0.0765 3.12 600 0.2052 11.2517
0.0424 3.65 700 0.2024 13.4490
0.0403 4.17 800 0.2094 12.0849
0.0216 4.69 900 0.2049 13.1959
0.0201 5.21 1000 0.2079 12.1034
0.0101 5.73 1100 0.2073 12.5663
0.0131 6.25 1200 0.2093 16.7757
0.0088 6.77 1300 0.2121 16.5165
0.0073 7.29 1400 0.2142 15.3314
0.0036 7.81 1500 0.2183 13.7020
0.0047 8.33 1600 0.2159 16.1647
0.0038 8.85 1700 0.2166 13.7514
0.0027 9.38 1800 0.2172 19.9975
0.0028 9.9 1900 0.2183 18.2385
0.0015 10.42 2000 0.2196 17.4238
0.0023 10.94 2100 0.2192 14.7019
0.0012 11.46 2200 0.2216 15.9919
0.0017 11.98 2300 0.2215 19.6334
0.001 12.5 2400 0.2219 20.5160
0.0014 13.02 2500 0.2236 21.7813
0.0011 13.54 2600 0.2242 23.0897
0.0009 14.06 2700 0.2276 25.0401
0.001 14.58 2800 0.2269 18.7014
0.001 15.1 2900 0.2265 20.8554
0.0008 15.62 3000 0.2272 19.7013
0.0009 16.15 3100 0.2277 26.5831
0.0007 16.67 3200 0.2290 24.3427
0.0008 17.19 3300 0.2285 20.7011
0.0007 17.71 3400 0.2288 21.8738
0.0007 18.23 3500 0.2290 20.7258
0.0006 18.75 3600 0.2295 21.1641
0.0006 19.27 3700 0.2297 23.7625
0.0007 19.79 3800 0.2301 24.4044
0.0006 20.31 3900 0.2299 22.9786
0.0006 20.83 4000 0.2300 23.0527

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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