Distilation_Whisper_base_CKP2

Baselhany/Distilation_Whisper_base_CKP2

Distilation_Whisper_base_CKP2 is a automatic speech recognition model from Baselhany. Use it when you need speech turned into text. It is set up for transformers. 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

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: whisper
Access: Public
Created: May 23, 2025
Updated: May 31, 2025
SHA: c50b3536

Base models

openai/whisper-base

Model card

From the Hugging Face model README

Whisper base AR - BA

This model is a fine-tuned version of openai/whisper-base on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:

Loss: 0.0949
Wer: 0.2085

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
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
46.3716	0.2851	400	0.1697	0.6098
16.3556	0.5701	800	0.1355	0.3556
11.9327	0.8552	1200	0.1230	0.3000
8.1222	1.1397	1600	0.1196	0.2543
6.2775	1.4247	2000	0.1165	0.2619
5.6861	1.7098	2400	0.1143	0.2390
5.238	1.9948	2800	0.1115	0.2346
4.5097	2.2794	3200	0.1107	0.2256
3.9677	2.5644	3600	0.1095	0.2262
3.8998	2.8495	4000	0.1085	0.2300
3.3351	3.1340	4400	0.1067	0.2140
3.1317	3.4190	4800	0.1067	0.2199
2.9814	3.7041	5200	0.1046	0.2119
3.167	3.9891	5600	0.1039	0.2104
2.498	4.2737	6000	0.1066	0.2177
2.8372	4.5587	6400	0.1022	0.2098
2.5573	4.8438	6800	0.1028	0.2181
2.3309	5.1283	7200	0.1006	0.2091
2.2589	5.4133	7600	0.1015	0.2100
2.1409	5.6984	8000	0.1024	0.2065
2.1048	5.9834	8400	0.0992	0.2138
1.8826	6.2679	8800	0.0987	0.2116
1.8778	6.5530	9200	0.0988	0.2073
2.0199	6.8381	9600	0.0981	0.2045
1.7238	7.1226	10000	0.0997	0.2022
1.8087	7.4076	10400	0.0983	0.2037
1.7075	7.6977	10800	0.0985	0.2059
1.7072	7.9827	11200	0.0977	0.2062
1.5864	8.2679	11600	0.0977	0.2066
1.6869	8.5530	12000	0.0972	0.2081
1.7383	8.8381	12400	0.0976	0.2041
1.4336	9.1226	12800	0.0970	0.2045
1.5429	9.4076	13200	0.0969	0.2010
1.5726	9.6927	13600	0.0969	0.2084
1.4709	9.9777	14000	0.0971	0.2044
1.5442	10.2637	14400	0.0978	0.2088
1.5764	10.5487	14800	0.0985	0.2151
1.6821	10.8338	15200	0.0970	0.2066
1.6529	11.1183	15600	0.0974	0.2082
1.5455	11.4033	16000	0.0971	0.2057
1.4845	11.6884	16400	0.0973	0.2140
1.4953	11.9735	16800	0.0960	0.2029
1.4349	12.2580	17200	0.0958	0.2009
1.4104	12.5430	17600	0.0974	0.2025
1.5073	12.8281	18000	0.0953	0.2044
1.2488	13.1126	18400	0.0949	0.1966
1.277	13.3976	18800	0.0955	0.2084
1.2443	13.6827	19200	0.0960	0.1995
1.3972	13.9678	19600	0.0955	0.2028
1.2847	14.2523	20000	0.0949	0.2034
1.3107	14.5373	20400	0.0951	0.2013
1.2232	14.8224	20800	0.0947	0.2003
1.2233	15.1069	21200	0.0949	0.1985
1.1999	15.3919	21600	0.0946	0.2025
1.236	15.6770	22000	0.0949	0.2029
1.2252	15.9621	22400	0.0945	0.1994
1.2094	16.2466	22800	0.0941	0.2050
1.2505	16.5316	23200	0.0941	0.2003
1.1193	16.8167	23600	0.0942	0.1991
1.1992	17.1062	24000	0.0946	0.2020
1.2794	17.3912	24400	0.0954	0.2118
1.2362	17.6763	24800	0.0948	0.2025
1.3528	17.9613	25200	0.0956	0.2070
1.1863	18.2459	25600	0.0935	0.2037
1.2936	18.5309	26000	0.0940	0.2032
1.2434	18.8160	26400	0.0938	0.2029
1.1254	19.1005	26800	0.0933	0.2026
1.2345	19.3855	27200	0.0934	0.2009
1.2177	19.6706	27600	0.0938	0.2037
1.1479	19.9556	28000	0.0938	0.2007
1.1077	20.2402	28400	0.0933	0.1995
1.1615	20.5252	28800	0.0931	0.2025
1.0642	20.8103	29200	0.0940	0.2045
1.0922	21.0948	29600	0.0935	0.2011
1.0885	21.3798	30000	0.0929	0.2010
1.107	21.6649	30400	0.0930	0.1988
1.0449	21.9499	30800	0.0931	0.2001
1.033	22.2345	31200	0.0931	0.2048
1.057	22.5195	31600	0.0932	0.1988
1.0248	22.8046	32000	0.0929	0.2019
0.9784	23.0891	32400	0.0927	0.1951
1.0443	23.3741	32800	0.0927	0.1995
0.9972	23.6592	33200	0.0923	0.1995
1.0527	23.9442	33600	0.0930	0.1964
0.9927	24.2288	34000	0.0927	0.1979
0.9504	24.5138	34400	0.0927	0.1960
1.0567	24.7989	34800	0.0925	0.1986
1.0316	25.0891	35200	0.0926	0.1983
0.9926	25.3741	35600	0.0928	0.1982
1.0646	25.6592	36000	0.0927	0.2006
1.0316	25.9442	36400	0.0929	0.2038
1.0315	26.2288	36800	0.0928	0.2022
1.0131	26.5138	37200	0.0927	0.2035
0.9659	26.7989	37600	0.0925	0.2000
1.0056	27.0834	38000	0.0922	0.1992
1.007	27.3684	38400	0.0922	0.1997
0.9602	27.6535	38800	0.0923	0.2017
0.9353	27.9385	39200	0.0923	0.1989
0.951	28.2231	39600	0.0920	0.1983
0.9675	28.5081	40000	0.0922	0.1969
0.9398	28.7932	40400	0.0922	0.1998
0.9533	29.0777	40800	0.0924	0.1976
0.9519	29.3627	41200	0.0922	0.1969
0.9297	29.6478	41600	0.0920	0.1982
0.9491	29.9328	42000	0.0920	0.1991

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
License: apache-2.0
Languages: ar
Created: May 23, 2025
Updated: May 31, 2025