whispertiny_buah25sil_v1_0

albertuspekerti/whispertiny_buah25sil_v1_0

whispertiny_buah25sil_v1_0 is a machine learning model from albertuspekerti. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

License: apache-2.0
Model type: whisper
Access: Public
Created: Feb 17, 2026
Updated: Feb 18, 2026
SHA: f4333535

Base models

openai/whisper-tiny

Model card

From the Hugging Face model README

whispertiny_buah25sil_v1_0

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

Loss: 0.0920
Wer: 6.3220

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-05
train_batch_size: 16
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: 500
training_steps: 150000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0286	0.0133	2000	0.9236	51.7270
0.0281	0.0267	4000	0.7050	33.3682
0.0452	0.04	6000	1.1925	361.7333
0.0166	0.0533	8000	0.7856	26.2717
0.0111	0.0667	10000	0.2461	23.1107
0.0221	1.0036	12000	0.3272	41.0509
0.0135	1.0169	14000	0.1464	15.0722
0.0088	1.0303	16000	0.1268	14.2139
0.014	1.0436	18000	0.1636	13.6697
0.0212	1.0569	20000	0.4627	45.1748
0.0214	1.0703	22000	0.1323	14.1511
0.01	2.0072	24000	0.0775	10.4878
0.0215	2.0205	26000	0.2208	22.0850
0.0178	2.0339	28000	0.1181	11.7019
0.0138	2.0472	30000	0.0929	10.8855
0.0133	0.0133	32000	0.1197	12.9579
0.009	0.0267	34000	0.1288	12.7277
0.0122	0.04	36000	0.2257	15.7840
0.0149	0.0533	38000	0.0972	10.9902
0.0073	0.0667	40000	0.0919	10.2366
0.0137	1.0036	42000	0.1876	20.2219
0.0074	1.0169	44000	0.1257	13.3347
0.0059	1.0303	46000	0.0835	9.0224
0.0093	1.0436	48000	0.1516	13.7325
0.0138	1.0569	50000	0.1355	13.2091
0.0109	1.0703	52000	0.1324	11.5554
0.0041	2.0072	54000	0.1019	10.1109
0.0133	2.0205	56000	0.2031	15.2397
0.0174	2.0339	58000	0.0869	11.0739
0.0092	2.0472	60000	0.0752	8.8549
0.0045	2.0605	62000	0.1778	13.5441
0.0048	2.0739	64000	0.0943	9.4829
0.0056	3.0108	66000	0.0719	8.2479
0.0042	3.0242	68000	0.1521	12.1834
0.009	3.0375	70000	0.0962	8.8759
0.0109	3.0508	72000	0.1341	12.5811
0.0067	3.0642	74000	0.0780	7.1174
0.0074	4.0011	76000	0.2035	15.6165
0.0088	4.0144	78000	0.0914	9.3573
0.0061	4.0278	80000	0.0972	8.6665
0.0047	4.0411	82000	0.1224	9.7969
0.0039	4.0544	84000	0.1238	9.9225
0.0046	4.0678	86000	0.0830	7.8501
0.0029	5.0047	88000	0.1433	11.0530
0.0038	5.0180	90000	0.0764	7.8920
0.006	5.0314	92000	0.0778	7.3686
0.0029	5.0447	94000	0.1064	8.3735
0.0042	5.0580	96000	0.1733	11.8694
0.0042	5.0714	98000	0.0746	6.6569
0.0042	6.0083	100000	0.0834	7.1174
0.0033	6.0216	102000	0.2858	17.7727
0.006	6.0350	104000	0.0943	7.7873
0.0011	6.0483	106000	0.0691	5.8196
0.0021	6.0616	108000	0.1403	9.7551
0.0008	6.0750	110000	0.0938	7.0965
0.0016	7.0119	112000	0.0783	6.4476
0.0035	7.0252	114000	0.0976	7.4733
0.0019	7.0386	116000	0.1210	8.5200
0.0024	7.0519	118000	0.0914	6.9500
0.002	7.0652	120000	0.0815	5.9242
0.0026	8.0022	122000	0.1309	8.8759
0.0028	8.0155	124000	0.0775	6.4685
0.0017	8.0289	126000	0.0949	6.7825
0.0008	8.0422	128000	0.1536	9.9853
0.0003	8.0555	130000	0.0769	5.7777
0.0008	8.0689	132000	0.0788	6.1336
0.0009	9.0058	134000	0.1596	9.6085
0.0002	9.0191	136000	0.0765	5.5893
0.003	9.0325	138000	0.0829	6.1964
0.0004	9.0458	140000	0.1211	7.8920
0.0007	9.0591	142000	0.1129	7.2640
0.0001	9.0725	144000	0.0823	5.8614
0.0042	10.0094	146000	0.1103	7.4105
0.0016	10.0227	148000	0.0912	6.5313
0.0004	10.0361	150000	0.0920	6.3220

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 4.0.0
Tokenizers 0.19.1

Type: whisper
License: apache-2.0
Created: Feb 17, 2026
Updated: Feb 18, 2026