whisper-small-0DB-3r6

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

• Cer: 38.6899
• Loss: 0.4287
• Wer: 84.8672

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: 3e-06
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• 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: 100
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Cer	Validation Loss	Wer
4.6407	1.2675	100	71.2115	1.1388	100.1235
2.9213	2.5350	200	45.1097	0.7472	92.2792
2.2742	3.8025	300	40.0584	0.6162	88.2644
1.8082	5.0637	400	40.1791	0.5245	85.2378
1.3140	6.3312	500	40.0885	0.4390	85.4849
1.1840	7.5987	600	39.2131	0.4320	85.0525
1.0385	8.8662	700	38.6899	0.4287	84.8672

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.3
• Tokenizers 0.22.2