sudoping01 / bambara-whisper-large

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Model's Last Updated: January 12 2025

Introduction of bambara-whisper-large

Model Details of bambara-whisper-large

bambara-whisper-large

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

  • Loss: 0.5315
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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 4
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
0.6556 1.0 1163 0.6901
0.5034 2.0 2326 0.5877
0.3637 3.0 3489 0.5327
0.2518 3.9970 4648 0.5315
Framework versions
  • PEFT 0.14.1.dev0
  • Transformers 4.49.0.dev0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

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