sarpba/whisper-small-cv17-hu-EV

Whisper Small Hu CV17 (ez a modell csak tesztelésre készült, a használata hibákat okozhat)

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0862
• Wer Ortho: 6.536794
• Wer: 5.627038

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: 2.5e-05
• train_batch_size: 64
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 6000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.3208	0.3298	250	0.3558	34.5839	31.0969
0.2542	0.6596	500	0.2683	27.2010	24.2218
0.2204	0.9894	750	0.2035	22.2962	19.4960
0.1301	1.3193	1000	0.1673	17.6683	15.2446
0.1171	1.6491	1250	0.1433	15.2445	12.9677
0.1075	1.9789	1500	0.1192	12.8658	10.7827
0.0492	2.3087	1750	0.1091	11.2489	9.1877
0.0491	2.6385	2000	0.1046	10.7582	9.0543
0.0472	2.9683	2250	0.0945	9.0750	7.5037
0.0203	3.2982	2500	0.0932	8.5873	7.2428
0.0188	3.6280	2750	0.0900	8.2019	6.9671
0.0183	3.9578	3000	0.0859	7.5154	6.4008
0.0068	4.2876	3250	0.0837	7.2052	6.1785
0.0064	4.6174	3500	0.0843	6.9613	6.0213
0.0061	4.9472	3750	0.0847	6.9674	5.9383
0.0025	5.2770	4000	0.0851	6.6994	5.7723
0.0023	5.6069	4250	0.0847	6.6331	5.6863
0.0022	5.9367	4500	0.0844	6.6211	5.7338
0.0014	6.2665	4750	0.0855	6.5789	5.6834
0.0011	6.5963	5000	0.0856	6.5609	5.6567
0.0012	6.9261	5250	0.0862	6.5368	5.6270
0.0009	7.2559	5500	0.0870	6.5699	5.6597
0.0009	7.5858	5750	0.0873	6.5639	5.6597
0.001	7.9156	6000	0.0873	6.5518	5.6389

Framework versions

• Transformers 4.41.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1