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JacobLinCool/whisper-large-v3-turbo-verbatim-1-lora

sourceHugging Facemitupdated 2y agoView on Hugging Face

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whisper-large-v3-turbo-verbatim-3-lora

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the JacobLinCool/ami-disfluent dataset. It achieves the following results on the evaluation set:

—Loss: 0.1459
—Wer: 7.7269
—Cer: 3.2519
—Decode Runtime: 111.0004
—Wer Runtime: 0.0705
—Cer Runtime: 0.0932

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: 5e-05
—trainbatchsize: 4
—evalbatchsize: 32
—seed: 42
—gradientaccumulationsteps: 16
—totaltrainbatch_size: 64
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—lrschedulerwarmup_steps: 100
—training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Decode Runtime	Wer Runtime	Cer Runtime
No log	0	0	2.2169	32.7209	17.9205	106.5404	0.0825	0.1203
0.1681	0.1	100	0.1998	9.9454	4.1038	108.1653	0.0730	0.0960
0.1025	0.2	200	0.1693	8.6885	3.7458	109.6779	0.0707	0.0957
0.2508	0.3	300	0.1590	8.3897	3.4931	110.3209	0.0716	0.0947
0.1446	1.088	400	0.1571	8.2626	3.4939	110.1930	0.0718	0.0951
0.1833	1.188	500	0.1505	8.0463	3.4298	110.3821	0.0709	0.0950
0.1409	1.288	600	0.1489	7.9948	3.3401	110.6880	0.0709	0.0939
0.1184	2.076	700	0.1492	7.9124	3.3181	110.6153	0.0728	0.0946
0.1737	2.176	800	0.1468	7.8128	3.2583	110.7120	0.0714	0.0947
0.1522	2.276	900	0.1462	7.7887	3.2604	110.7694	0.0710	0.0937
0.1077	3.064	1000	0.1459	7.7269	3.2519	111.0004	0.0705	0.0932

Framework versions

—PEFT 0.14.0
—Transformers 4.48.0
—Pytorch 2.4.1+cu124
—Datasets 3.2.0
—Tokenizers 0.21.0