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Whisper largeV2 Italian MLS

This model is a fine-tuned version of openai/whisper-large-v2 on the facebook/multilingual_librispeech italian dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2051
  • Wer: 8.3353

Model description

The model is fine-tuned for 4000 updates/steps on multilingual librispeech Italian train data.

  • Zero-shot - 13.8 (MLS Italian test)
  • Fine-tune MLS Italian train - 8.33 (MLS Italian test) (-40%)

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: 32
  • eval_batch_size: 8
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1115 1.02 1000 0.2116 9.4217
0.0867 2.03 2000 0.1964 9.7823
0.0447 3.05 3000 0.2001 9.6409
0.0426 4.07 4000 0.2051 8.3353

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train sgangireddy/whisper-largev2-mls-it

Evaluation results