whisper-bn

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whisper-bn

This model is a fine-tuned version of bangla-speech-processing/BanglaASR on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0709
• eval_wer: 24.0044
• eval_levenshtein_similarity: 0.8521
• eval_runtime: 153.8315
• eval_samples_per_second: 2.178
• eval_steps_per_second: 0.273
• epoch: 7.0
• step: 2639

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
• optimizer: Use OptimizerNames.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: 500
• num_epochs: 10
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.2