whisper-large-v3-turbo-l21l30

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9327
• Wer: 39.1887

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• 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: 2000
• training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0	0	5.7681	1174.3994
0.8929	4.0112	2000	1.1186	45.0571
0.6935	9.0002	4000	0.9811	50.2954
0.7716	13.0114	6000	0.9477	44.3482
0.6844	18.0004	8000	0.9464	43.5605
0.5635	22.0116	10000	0.9372	40.1339
0.7053	27.0006	12000	0.9368	42.7727
0.515	31.0118	14000	0.9355	40.0945
0.5938	36.0008	16000	0.9333	39.5825
0.734	40.012	18000	0.9320	39.3068
0.6472	45.001	20000	0.9327	39.1887

Framework versions

• Transformers 4.54.0
• Pytorch 2.8.0.dev20250319+cu128
• Datasets 3.6.0
• Tokenizers 0.21.2