Hanhpt23/whisper-small-germanmed-free_ED0-8

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the Hanhpt23/GermanMed-full dataset. It achieves the following results on the evaluation set:

• Loss: 0.6502
• Wer: 22.8325
• Cer: 15.2331

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
0.4898	1.0	194	0.4951	31.3586	21.1891
0.2315	2.0	388	0.4999	33.0968	22.6097
0.1009	3.0	582	0.5097	29.4456	19.8430
0.0558	4.0	776	0.5487	27.8412	19.0253
0.0379	5.0	970	0.5783	28.7566	19.9297
0.0232	6.0	1164	0.5849	24.9203	16.3505
0.0136	7.0	1358	0.5879	27.7486	19.3562
0.0143	8.0	1552	0.6237	25.2700	17.6567
0.0036	9.0	1746	0.6323	26.4939	18.1002
0.0035	10.0	1940	0.6338	26.5762	18.5022
0.0045	11.0	2134	0.6337	23.3364	15.9694
0.0041	12.0	2328	0.6363	23.6655	16.0144
0.0004	13.0	2522	0.6397	22.1125	14.6475
0.0002	14.0	2716	0.6415	22.7502	15.1846
0.0002	15.0	2910	0.6443	22.7193	15.1742
0.0002	16.0	3104	0.6461	22.7296	15.1915
0.0001	17.0	3298	0.6477	22.6885	15.1777
0.0002	18.0	3492	0.6490	22.6782	15.1586
0.0001	19.0	3686	0.6499	22.7296	15.1673
0.0001	20.0	3880	0.6502	22.8325	15.2331

Framework versions

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