Hanhpt23/whisper-small-vietmed-free_ED3-11

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the pphuc25/VietMed-split-8-2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.8783
• Wer: 84.0710
• Cer: 69.8088

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.5701	1.0	569	0.5608	46.2200	38.1533
0.4525	2.0	1138	0.5395	65.0522	58.3991
0.3578	3.0	1707	0.5448	46.9632	42.0497
0.267	4.0	2276	0.5691	40.8786	36.0588
0.1655	5.0	2845	0.6143	74.4609	62.7468
0.0965	6.0	3414	0.6592	66.0443	49.6775
0.0465	7.0	3983	0.7106	64.5982	55.2552
0.0222	8.0	4552	0.7337	75.1455	63.4091
0.0162	9.0	5121	0.7609	57.3787	49.1906
0.0071	10.0	5690	0.7812	65.8429	53.4811
0.0048	11.0	6259	0.7982	49.3355	40.4222
0.0048	12.0	6828	0.8064	53.4249	43.6294
0.0023	13.0	7397	0.8291	55.4347	44.3160
0.0032	14.0	7966	0.8303	63.7196	56.2369
0.0013	15.0	8535	0.8443	83.7342	69.0423
0.0034	16.0	9104	0.8523	88.0871	73.9847
0.0009	17.0	9673	0.8752	85.7148	69.7958
0.0004	18.0	10242	0.8713	90.1885	72.8172
0.0004	19.0	10811	0.8762	82.5773	68.7490
0.0003	20.0	11380	0.8783	84.0710	69.8088

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1