whisper-large-v3-Bengali-Version1

This model is a fine-tuned version of openai/whisper-large-v3 on the fleurs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1519
  • Wer: 44.5003

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: 3e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2412 4.8193 2000 0.2103 56.7927
0.208 9.6386 4000 0.1844 51.9640
0.195 14.4578 6000 0.1719 49.3167
0.194 19.2771 8000 0.1647 47.7358
0.1762 24.0964 10000 0.1597 46.6144
0.1763 28.9157 12000 0.1567 45.8361
0.168 33.7349 14000 0.1544 45.1192
0.1623 38.5542 16000 0.1530 44.8802
0.1601 43.3735 18000 0.1521 44.7822
0.1666 48.1928 20000 0.1519 44.5003

Framework versions

  • PEFT 0.12.1.dev0
  • Transformers 4.45.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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