Whisper medium LV - Felikss Kleins

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2416
  • Wer: 11.9387

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.02 200 0.2930 22.3576
0.9797 1.0116 400 0.2359 18.2083
0.357 2.0033 600 0.2274 16.4665
0.2582 2.0233 800 0.2111 15.6402
0.1718 3.0149 1000 0.2135 14.9883
0.1718 4.0066 1200 0.2090 14.2294
0.1355 4.0266 1400 0.2193 13.5537
0.1024 5.0183 1600 0.2255 14.5048
0.0836 6.0099 1800 0.2145 12.9751
0.0699 7.0015 2000 0.2232 13.2129
0.0699 7.0216 2200 0.2181 12.7155
0.0598 8.0132 2400 0.2192 12.7076
0.054 9.0048 2600 0.2348 13.0048
0.0452 9.0249 2800 0.2241 13.0940
0.0433 10.0165 3000 0.2406 12.6362
0.0433 11.0082 3200 0.2283 12.5332
0.0377 11.0282 3400 0.2293 12.2201
0.0317 12.0198 3600 0.2323 12.6144
0.0297 13.0114 3800 0.2309 12.2974
0.0267 14.0031 4000 0.2342 11.9011
0.0267 14.0231 4200 0.2286 12.1171
0.0243 15.0147 4400 0.2364 12.0854
0.0218 16.0064 4600 0.2405 12.1805
0.021 16.0264 4800 0.2422 12.0338
0.0173 17.0180 5000 0.2416 11.9387

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.0.1
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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Evaluation results