metaasr-1-b-mcv-11-v-1

badili/metaasr-1-b-mcv-11-v-1

metaasr-1-b-mcv-11-v-1 is a automatic speech recognition model from badili. 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: Apr 29, 2023
Updated: May 3, 2023
SHA: 8c1be54c

Datasets

common_voice_11_0

Model card

From the Hugging Face model README

wav2vec2-large-xls-r-1b-swahili-v12

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.4658
Wer: 0.2038

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
2.726	0.35	400	0.7214	0.6674
0.5241	0.69	800	0.5641	0.5345
0.4616	1.04	1200	0.5112	0.4755
0.4018	1.39	1600	0.4797	0.4158
0.3916	1.74	2000	0.4483	0.3985
0.3661	2.08	2400	0.4449	0.3931
0.3314	2.43	2800	0.4124	0.3549
0.3287	2.78	3200	0.4008	0.3651
0.317	3.13	3600	0.4460	0.3735
0.3026	3.47	4000	0.4165	0.3753
0.3061	3.82	4400	0.4112	0.3550
0.2808	4.17	4800	0.3951	0.3275
0.2641	4.52	5200	0.3934	0.3340
0.2709	4.86	5600	0.3963	0.3287
0.2586	5.21	6000	0.4114	0.3396
0.2487	5.56	6400	0.3821	0.3214
0.2618	5.91	6800	0.3987	0.3268
0.2297	6.25	7200	0.3810	0.3132
0.2337	6.6	7600	0.3740	0.3131
0.2285	6.95	8000	0.3715	0.3093
0.2173	7.29	8400	0.3878	0.3147
0.2251	7.64	8800	0.3862	0.3134
0.2215	7.99	9200	0.3621	0.2940
0.195	8.34	9600	0.3651	0.3005
0.201	8.68	10000	0.3837	0.3167
0.1964	9.03	10400	0.3719	0.2876
0.1741	9.38	10800	0.3637	0.2840
0.181	9.73	11200	0.3616	0.2914
0.1795	10.07	11600	0.3719	0.2753
0.1602	10.42	12000	0.3618	0.2856
0.1753	10.77	12400	0.3570	0.2788
0.1627	11.12	12800	0.3500	0.2719
0.1566	11.46	13200	0.3553	0.2808
0.1589	11.81	13600	0.3635	0.2699
0.1511	12.16	14000	0.3656	0.2692
0.1451	12.51	14400	0.3759	0.2759
0.1444	12.85	14800	0.3607	0.2677
0.1359	13.2	15200	0.3852	0.2660
0.1313	13.55	15600	0.3587	0.2679
0.1329	13.89	16000	0.3548	0.2584
0.1163	14.24	16400	0.3701	0.2535
0.1175	14.59	16800	0.3693	0.2638
0.1242	14.94	17200	0.3660	0.2565
0.1067	15.28	17600	0.3835	0.2581
0.1077	15.63	18000	0.3799	0.2504
0.1099	15.98	18400	0.3598	0.2478
0.0952	16.33	18800	0.3865	0.2563
0.1007	16.67	19200	0.3630	0.2565
0.0999	17.02	19600	0.3912	0.2505
0.0895	17.37	20000	0.3934	0.2631
0.0974	17.72	20400	0.3718	0.2462
0.0939	18.06	20800	0.4001	0.2587
0.0915	18.41	21200	0.4048	0.2468
0.0865	18.76	21600	0.3860	0.2415
0.0784	19.11	22000	0.4148	0.2454
0.0782	19.45	22400	0.3952	0.2471
0.0775	19.8	22800	0.3943	0.2434
0.0735	20.15	23200	0.4093	0.2405
0.0679	20.5	23600	0.3996	0.2362
0.0677	20.84	24000	0.4133	0.2365
0.0687	21.19	24400	0.4303	0.2330
0.0651	21.54	24800	0.4288	0.2326
0.0647	21.88	25200	0.4134	0.2347
0.0634	22.23	25600	0.4148	0.2312
0.0592	22.58	26000	0.4322	0.2315
0.06	22.93	26400	0.4050	0.2313
0.0561	23.27	26800	0.4260	0.2263
0.0546	23.62	27200	0.4228	0.2238
0.0548	23.97	27600	0.4140	0.2258
0.0505	24.32	28000	0.4304	0.2246
0.0501	24.66	28400	0.4241	0.2233
0.0481	25.01	28800	0.4385	0.2209
0.0469	25.36	29200	0.4451	0.2189
0.0464	25.71	29600	0.4397	0.2217
0.0438	26.05	30000	0.4419	0.2154
0.0432	26.4	30400	0.4366	0.2137
0.0419	26.75	30800	0.4371	0.2137
0.0419	27.1	31200	0.4552	0.2109
0.0392	27.44	31600	0.4496	0.2108
0.0386	27.79	32000	0.4585	0.2096
0.0387	28.14	32400	0.4496	0.2065
0.0367	28.48	32800	0.4646	0.2082
0.0357	28.83	33200	0.4553	0.2067
0.0355	29.18	33600	0.4615	0.2055
0.0345	29.53	34000	0.4670	0.2046
0.0346	29.87	34400	0.4658	0.2038

Framework versions

Transformers 4.29.0.dev0
Pytorch 2.0.0+cu117
Datasets 2.12.0
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Apr 29, 2023
Updated: May 3, 2023