Modelpublic

HouraMor/wh-ft-lr1e6-dtstf5-adm-ga1ba16-st15k-pat3-v2-evalstp500

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face

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Model Card

wh-ft-lr1e6-dtstf5-adm-ga1ba16-st15k-pat3-v2-evalstp500

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

—Loss: 0.4612
—Wer: 0.2256
—Cer: 0.1658

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
—trainbatchsize: 16
—evalbatchsize: 8
—seed: 42
—optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—lrschedulerwarmup_steps: 750
—training_steps: 15000
—mixedprecisiontraining: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.6297	0.3047	500	0.5828	0.2892	0.2118
0.5115	0.6094	1000	0.5015	0.2713	0.2022
0.4822	0.9141	1500	0.4747	0.2612	0.1963
0.4142	1.2188	2000	0.4649	0.2427	0.1738
0.4002	1.5235	2500	0.4579	0.2336	0.1747
0.4238	1.8282	3000	0.4510	0.2306	0.1722
0.3308	2.1328	3500	0.4535	0.2229	0.1629
0.3061	2.4375	4000	0.4523	0.2370	0.1748
0.3301	2.7422	4500	0.4478	0.2266	0.1663
0.2867	3.0469	5000	0.4540	0.2457	0.1822
0.2672	3.3516	5500	0.4616	0.2449	0.1811
0.2822	3.6563	6000	0.4612	0.2256	0.1658

Framework versions

—Transformers 4.52.3
—Pytorch 2.7.0+cu118
—Datasets 3.5.1
—Tokenizers 0.21.1