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Whisper_small_Somali

This model is a fine-tuned version of openai/whisper-small on the google/fleurs so_so dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0764
  • Wer: 66.5950

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: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • 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: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0205 30.74 400 1.8418 67.2524
0.0012 61.52 800 2.0764 66.5950
0.0006 92.3 1200 2.1537 67.6452
0.0004 123.07 1600 2.1930 67.1367
0.0004 153.81 2000 2.2065 66.9299

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train steja/whisper-small-somali

Evaluation results