npallewela/whisper-small-ap2

Whisper small ap2 - Nuwan

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

• Loss: 0.5955
• Wer Ortho: 34.8080
• Wer: 34.1567

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-06
• train_batch_size: 16
• eval_batch_size: 16
• 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: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 6000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
2.2182	0.1642	400	2.3026	80.3514	78.8883
0.8087	0.3284	800	0.8213	70.8486	69.5550
0.7561	0.4926	1200	0.7547	50.8240	49.9130
0.7118	0.6568	1600	0.7234	47.8373	47.0305
0.6374	0.8210	2000	0.7005	45.7117	44.8588
0.6521	0.9852	2400	0.6818	45.0158	44.1598
0.6017	1.1494	2800	0.6670	45.6405	44.8369
0.5899	1.3136	3200	0.6565	41.7684	41.0111
0.5954	1.4778	3600	0.6458	44.0289	43.3934
0.5406	1.6420	4000	0.6323	40.5343	39.7944
0.4964	1.8062	4400	0.6231	38.2753	37.6519
0.5695	1.9704	4800	0.6130	39.6655	38.9257
0.4507	2.1346	5200	0.6077	37.3778	36.6238
0.409	2.2989	5600	0.6014	34.6367	33.9242
0.4788	2.4631	6000	0.5955	34.8080	34.1567

Framework versions

• Transformers 4.57.1
• Pytorch 2.9.0+cu126
• Datasets 3.6.0
• Tokenizers 0.22.1