deepdml/whisper-small-af-fleurs-norm

Whisper Small af

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

• Loss: 0.8630
• Wer: 32.0866
• Cer: 11.9814

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.04
• training_steps: 600

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.3398	1.0583	100	0.8004	32.3290	11.4301
0.1013	3.0083	200	0.7973	31.9307	12.0576
0.0341	4.0667	300	0.8230	30.5281	11.0694
0.0136	6.0167	400	0.8477	32.8485	12.2775
0.0093	7.075	500	0.8606	33.5931	13.3537
0.0068	9.025	600	0.8630	32.0866	11.9814

Framework versions

• Transformers 4.42.0.dev0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1

Citation

Please cite the model using the following BibTeX entry:

@misc{deepdml/whisper-small-af-fleurs-norm,
      title={Fine-tuned Whisper small ASR model for speech recognition in Afrikaans},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-small-af-fleurs-norm}},
      year={2026}
    }