whisper-small-ml

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: 0.0159
• Wer: 10.5437

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: 16
• eval_batch_size: 8
• seed: 42
• 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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2000	3.3784	1000	0.2324	81.7581
0.0773	6.7568	2000	0.0902	53.6331
0.0214	10.1351	3000	0.0310	19.7663
0.0110	13.5135	4000	0.0159	10.5437

Framework versions

• Transformers 5.22.1
• Pytorch 2.11.0+cu130
• Datasets 5.1.0
• Tokenizers 0.23.3