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finetune_v3

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metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: finetune_v3
    results: []

finetune_v3

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1775
  • Wer: 13.8249

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • training_steps: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 6.6667 10 0.2449 19.8157
No log 13.3333 20 0.1967 14.5161
No log 20.0 30 0.1821 14.2857
No log 26.6667 40 0.1775 13.8249

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.2.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1