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whisper-base-full-data-v4

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

  • Loss: 0.2221

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
  • distributed_type: tpu
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 256
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5000
  • training_steps: 63840

Training results

Training Loss Epoch Step Validation Loss
0.2569 1.57 5000 0.4138
0.1774 3.13 10000 0.3295
0.1485 4.7 15000 0.2936
0.1316 6.27 20000 0.2745
0.1187 7.83 25000 0.2599
0.1037 9.4 30000 0.2496
0.1011 10.97 35000 0.2407
0.0905 12.53 40000 0.2356
0.0827 14.1 45000 0.2316
0.0789 15.67 50000 0.2278
0.0741 17.23 55000 0.2248
0.0714 18.8 60000 0.2228

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.1.0a0+gitcc01568
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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