sudoping01 / maliba-asr-v0

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Model's Last Updated: March 16 2025

Introduction of maliba-asr-v0

Model Details of maliba-asr-v0

maliba-asr-v0

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: 0.2265
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: 6
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
0.4581 0.9998 3502 0.2683
0.3656 1.9998 7004 0.2527
0.3463 2.9998 10506 0.2447
0.2788 3.9998 14008 0.2405
0.2607 4.9998 17510 0.2277
0.202 5.9998 21012 0.2265
Framework versions
  • PEFT 0.14.1.dev0
  • Transformers 4.50.0.dev0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

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