Hanhpt23/whisper-small-vietmed-free_E0-8

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: 0.9214
• Wer: 21.2777
• Cer: 17.6019

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
0.624	1.0	569	0.6172	28.3507	24.2846
0.4335	2.0	1138	0.5851	24.6604	20.0193
0.2821	3.0	1707	0.6146	24.1333	19.6217
0.1837	4.0	2276	0.6578	24.6458	20.3639
0.0938	5.0	2845	0.7273	24.2724	19.7762
0.0787	6.0	3414	0.7621	23.7232	19.1921
0.0536	7.0	3983	0.8131	23.9649	19.5506
0.0424	8.0	4552	0.8392	24.1552	19.7242
0.0205	9.0	5121	0.8504	22.8409	18.6722
0.018	10.0	5690	0.8700	23.0240	18.7208
0.016	11.0	6259	0.8755	22.8666	18.6357
0.0152	12.0	6828	0.8713	22.5773	18.3892
0.0062	13.0	7397	0.8858	21.9623	18.0203
0.0051	14.0	7966	0.9012	21.9001	18.0021
0.0024	15.0	8535	0.8900	21.7133	17.8484
0.001	16.0	9104	0.9155	21.9586	18.0594
0.0006	17.0	9673	0.9122	21.5047	17.7451
0.0005	18.0	10242	0.9147	21.2997	17.5880
0.0011	19.0	10811	0.9194	21.3143	17.6132
0.0001	20.0	11380	0.9214	21.2777	17.6019

Framework versions

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