wav2vec2-common_voice-tr-demo

utakumi/wav2vec2-common_voice-tr-demo

wav2vec2-common_voice-tr-demo is a automatic speech recognition model from utakumi. 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: wav2vec2
Access: Public
Created: Dec 1, 2024
Updated: Dec 3, 2024
SHA: 3938d2e1

Base models

facebook/wav2vec2-large-xlsr-53

Datasets

common_voice_13_0

Model card

From the Hugging Face model README

wav2vec2-common_voice-tr-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - TR dataset. It achieves the following results on the evaluation set:

Loss: 0.3097
Wer: 0.4725

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use 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: 15.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.0763	100	3.9145	1.0
No log	0.1526	200	3.1491	1.0
No log	0.2289	300	2.4589	1.0151
No log	0.3052	400	0.8488	0.9319
4.6713	0.3815	500	0.7336	0.9263
4.6713	0.4578	600	0.6043	0.8163
4.6713	0.5341	700	0.5496	0.7753
4.6713	0.6105	800	0.5273	0.7605
4.6713	0.6868	900	0.5153	0.7516
0.509	0.7631	1000	0.4648	0.7192
0.509	0.8394	1100	0.4232	0.6961
0.509	0.9157	1200	0.4227	0.6983
0.509	0.9920	1300	0.4336	0.6945
0.509	1.0679	1400	0.4217	0.6709
0.37	1.1442	1500	0.4050	0.6767
0.37	1.2205	1600	0.4036	0.6879
0.37	1.2968	1700	0.3946	0.6651
0.37	1.3731	1800	0.3887	0.6583
0.37	1.4494	1900	0.3976	0.6819
0.3179	1.5258	2000	0.3707	0.6320
0.3179	1.6021	2100	0.3758	0.6387
0.3179	1.6784	2200	0.3636	0.6324
0.3179	1.7547	2300	0.3880	0.6593
0.3179	1.8310	2400	0.3533	0.6304
0.3065	1.9073	2500	0.3608	0.6312
0.3065	1.9836	2600	0.3474	0.6154
0.3065	2.0595	2700	0.3638	0.6165
0.3065	2.1358	2800	0.3606	0.6085
0.3065	2.2121	2900	0.3374	0.6053
0.2597	2.2884	3000	0.3315	0.6051
0.2597	2.3647	3100	0.3499	0.6164
0.2597	2.4411	3200	0.3410	0.6064
0.2597	2.5174	3300	0.3465	0.6099
0.2597	2.5937	3400	0.3382	0.6009
0.2536	2.6700	3500	0.3367	0.6025
0.2536	2.7463	3600	0.3397	0.6056
0.2536	2.8226	3700	0.3341	0.5914
0.2536	2.8989	3800	0.3267	0.5887
0.2536	2.9752	3900	0.3312	0.5836
0.2372	3.0511	4000	0.3317	0.5821
0.2372	3.1274	4100	0.3258	0.5747
0.2372	3.2037	4200	0.3350	0.5808
0.2372	3.2800	4300	0.3392	0.5798
0.2372	3.3564	4400	0.3209	0.5779
0.2128	3.4327	4500	0.3227	0.5719
0.2128	3.5090	4600	0.3217	0.5740
0.2128	3.5853	4700	0.3210	0.5713
0.2128	3.6616	4800	0.3093	0.5662
0.2128	3.7379	4900	0.3242	0.5701
0.2114	3.8142	5000	0.3142	0.5646
0.2114	3.8905	5100	0.3135	0.5680
0.2114	3.9668	5200	0.3219	0.5646
0.2114	4.0427	5300	0.3347	0.5610
0.2114	4.1190	5400	0.3303	0.5682
0.1987	4.1953	5500	0.3368	0.5690
0.1987	4.2717	5600	0.3214	0.5629
0.1987	4.3480	5700	0.3072	0.5621
0.1987	4.4243	5800	0.3213	0.5606
0.1987	4.5006	5900	0.3184	0.5711
0.1889	4.5769	6000	0.3135	0.5601
0.1889	4.6532	6100	0.3201	0.5596
0.1889	4.7295	6200	0.3049	0.5567
0.1889	4.8058	6300	0.3081	0.5545
0.1889	4.8821	6400	0.3112	0.5569
0.183	4.9584	6500	0.3060	0.5504
0.183	5.0343	6600	0.3161	0.5569
0.183	5.1106	6700	0.3288	0.5550
0.183	5.1870	6800	0.3199	0.5502
0.183	5.2633	6900	0.3248	0.5558
0.1648	5.3396	7000	0.3216	0.5566
0.1648	5.4159	7100	0.3026	0.5543
0.1648	5.4922	7200	0.3135	0.5611
0.1648	5.5685	7300	0.3137	0.5582
0.1648	5.6448	7400	0.3179	0.5566
0.161	5.7211	7500	0.3256	0.5522
0.161	5.7974	7600	0.3109	0.5553
0.161	5.8737	7700	0.3047	0.5430
0.161	5.9500	7800	0.3128	0.5436
0.161	6.0259	7900	0.3150	0.5427
0.1564	6.1023	8000	0.3025	0.5405
0.1564	6.1786	8100	0.3155	0.5533
0.1564	6.2549	8200	0.3101	0.5377
0.1564	6.3312	8300	0.3302	0.5407
0.1564	6.4075	8400	0.3180	0.5361
0.1454	6.4838	8500	0.3060	0.5397
0.1454	6.5601	8600	0.3084	0.5347
0.1454	6.6364	8700	0.3218	0.5443
0.1454	6.7127	8800	0.3086	0.5433
0.1454	6.7890	8900	0.3248	0.5337
0.1425	6.8653	9000	0.2960	0.5370
0.1425	6.9416	9100	0.2962	0.5367
0.1425	7.0176	9200	0.3222	0.5313
0.1425	7.0939	9300	0.3115	0.5329
0.1425	7.1702	9400	0.3048	0.5261
0.1352	7.2465	9500	0.3170	0.5269
0.1352	7.3228	9600	0.2940	0.5186
0.1352	7.3991	9700	0.3054	0.5236
0.1352	7.4754	9800	0.3175	0.5262
0.1352	7.5517	9900	0.2949	0.5267
0.1297	7.6280	10000	0.3060	0.5255
0.1297	7.7043	10100	0.2849	0.5254
0.1297	7.7806	10200	0.2876	0.5240
0.1297	7.8569	10300	0.2971	0.5172
0.1297	7.9332	10400	0.3026	0.5179
0.1277	8.0092	10500	0.2984	0.5161
0.1277	8.0855	10600	0.3032	0.5241
0.1277	8.1618	10700	0.3111	0.5218
0.1277	8.2381	10800	0.2936	0.5216
0.1277	8.3144	10900	0.2961	0.5129
0.1168	8.3907	11000	0.3053	0.5126
0.1168	8.4670	11100	0.2934	0.5134
0.1168	8.5433	11200	0.3029	0.5145
0.1168	8.6196	11300	0.3097	0.5153
0.1168	8.6959	11400	0.2979	0.5128
0.1149	8.7722	11500	0.2925	0.5146
0.1149	8.8485	11600	0.3051	0.5169
0.1149	8.9248	11700	0.3001	0.5126
0.1149	9.0008	11800	0.2969	0.5063
0.1149	9.0771	11900	0.3101	0.5083
0.1076	9.1534	12000	0.3153	0.5171
0.1076	9.2297	12100	0.3266	0.5200
0.1076	9.3060	12200	0.3139	0.5173
0.1076	9.3823	12300	0.3133	0.5172
0.1076	9.4586	12400	0.3073	0.5225
0.0988	9.5349	12500	0.3108	0.5160
0.0988	9.6112	12600	0.3038	0.5265
0.0988	9.6875	12700	0.2941	0.5110
0.0988	9.7638	12800	0.2985	0.5013
0.0988	9.8401	12900	0.2984	0.5099
0.103	9.9164	13000	0.3067	0.5174
0.103	9.9928	13100	0.2915	0.5039
0.103	10.0687	13200	0.2970	0.5034
0.103	10.1450	13300	0.3185	0.5169
0.103	10.2213	13400	0.3166	0.5052
0.0925	10.2976	13500	0.3081	0.5068
0.0925	10.3739	13600	0.3048	0.5103
0.0925	10.4502	13700	0.3028	0.5000
0.0925	10.5265	13800	0.3043	0.5043
0.0925	10.6028	13900	0.3030	0.4949
0.0909	10.6791	14000	0.2920	0.4975
0.0909	10.7554	14100	0.3046	0.4992
0.0909	10.8317	14200	0.3047	0.5025
0.0909	10.9081	14300	0.2946	0.4972
0.0909	10.9844	14400	0.2917	0.4996
0.0884	11.0603	14500	0.3081	0.5003
0.0884	11.1366	14600	0.3083	0.4955
0.0884	11.2129	14700	0.3057	0.4937
0.0884	11.2892	14800	0.3083	0.4987
0.0884	11.3655	14900	0.3074	0.4962
0.0798	11.4418	15000	0.2997	0.4956
0.0798	11.5181	15100	0.2995	0.4990
0.0798	11.5944	15200	0.2942	0.4926
0.0798	11.6707	15300	0.2961	0.4880
0.0798	11.7470	15400	0.3124	0.4902
0.0803	11.8233	15500	0.2986	0.4894
0.0803	11.8997	15600	0.2985	0.4902
0.0803	11.9760	15700	0.3027	0.4963
0.0803	12.0519	15800	0.3083	0.4878
0.0803	12.1282	15900	0.2997	0.4869
0.0781	12.2045	16000	0.3017	0.4911
0.0781	12.2808	16100	0.3071	0.4881
0.0781	12.3571	16200	0.3135	0.4893
0.0781	12.4334	16300	0.3038	0.4859
0.0781	12.5097	16400	0.3072	0.4845
0.0721	12.5860	16500	0.3146	0.4840
0.0721	12.6623	16600	0.3058	0.4839
0.0721	12.7386	16700	0.3020	0.4816
0.0721	12.8150	16800	0.3081	0.4811
0.0721	12.8913	16900	0.3005	0.4798
0.0701	12.9676	17000	0.3087	0.4836
0.0701	13.0435	17100	0.3191	0.4888
0.0701	13.1198	17200	0.3174	0.4839
0.0701	13.1961	17300	0.3073	0.4846
0.0701	13.2724	17400	0.3044	0.4812
0.0625	13.3487	17500	0.3117	0.4788
0.0625	13.4250	17600	0.3130	0.4782
0.0625	13.5013	17700	0.3029	0.4764
0.0625	13.5776	17800	0.3101	0.4812
0.0625	13.6539	17900	0.2972	0.4814
0.0627	13.7303	18000	0.3097	0.4764
0.0627	13.8066	18100	0.3035	0.4761
0.0627	13.8829	18200	0.3074	0.4775
0.0627	13.9592	18300	0.3059	0.4755
0.0627	14.0351	18400	0.3084	0.4755
0.0623	14.1114	18500	0.3097	0.4778
0.0623	14.1877	18600	0.3160	0.4770
0.0623	14.2640	18700	0.3148	0.4762
0.0623	14.3403	18800	0.3184	0.4737
0.0623	14.4166	18900	0.3177	0.4750
0.0554	14.4929	19000	0.3141	0.4744
0.0554	14.5692	19100	0.3114	0.4746
0.0554	14.6456	19200	0.3114	0.4736
0.0554	14.7219	19300	0.3094	0.4736
0.0554	14.7982	19400	0.3086	0.4727
0.0553	14.8745	19500	0.3094	0.4722
0.0553	14.9508	19600	0.3097	0.4720

Framework versions

Transformers 4.47.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Languages: tr
Created: Dec 1, 2024
Updated: Dec 3, 2024