swahili-distill_smoke-20260709-152928

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.2642
• Wer: 92.2175
• Cer: 35.3085
• Avg Pred Words: 32.51
• Avg Ref Words: 33.28

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 OptimizerNames.ADAMW_TORCH_FUSED 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
• training_steps: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Avg Pred Words	Avg Ref Words
2.997	1.5714	25	3.4215	102.3137	38.3373	34.21	33.28
2.7464	3.1270	50	3.0001	105.6190	39.4960	36.69	33.28
2.4057	4.6984	75	2.6360	101.9231	43.6317	34.85	33.28
2.0697	6.2540	100	2.2642	92.2175	35.3085	32.51	33.28

Framework versions

• Transformers 4.57.6
• Pytorch 2.10.0+cu128
• Datasets 3.6.0
• Tokenizers 0.22.2