sudoping01 / bambara-whisper-large-v5

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Model's Last Updated: January 15 2025

Introduction of bambara-whisper-large-v5

Model Details of bambara-whisper-large-v5

bambara-whisper-large-v5

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: 1.0897
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: 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: cosine_with_restarts
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 6
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
2.5664 0.2674 250 2.3071
1.9725 0.5348 500 2.0162
1.579 0.8021 750 1.4457
1.4458 1.0695 1000 1.3399
1.3508 1.3369 1250 1.2798
1.3225 1.6043 1500 1.2372
1.2974 1.8717 1750 1.2088
1.2617 2.1390 2000 1.1850
1.2305 2.4064 2250 1.1643
1.2392 2.6738 2500 1.1466
1.2395 2.9412 2750 1.1342
1.1663 3.2086 3000 1.1249
1.1967 3.4759 3250 1.1139
1.1624 3.7433 3500 1.1087
1.1527 4.0107 3750 1.1031
1.1512 4.2781 4000 1.0985
1.1589 4.5455 4250 1.0945
1.1547 4.8128 4500 1.0926
1.1334 5.0802 4750 1.0919
1.1688 5.3476 5000 1.0903
1.1324 5.6150 5250 1.0898
1.1735 5.8824 5500 1.0897
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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