ymoslem/whisper-small-bemba-v1

whisper-small-bem-v1

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

• Loss: 0.4645
• Wer: 36.1826

When combined with fine-tuned NLLB-200 3.3B, Bemba-English results are as follows:

BLEU	ChrF++	COMET
27.41	49.65	51.77

Model description

Bemba automatic speech recognition (ASR)

Intended uses & limitations

For research purposes only

Training and evaluation data

Big-C

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• 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_ratio: 0.03
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5933	1.0	10645	0.5593	44.3113
0.4243	2.0	21290	0.4738	38.8064
0.2944	3.0	31935	0.4645	36.1826

Framework versions

• Transformers 4.51.3
• Pytorch 2.4.1+cu124
• Datasets 3.5.1
• Tokenizers 0.21.1