Kinyarwanda

MheniDevs/Kinyarwanda

Kinyarwanda is a automatic speech recognition model from MheniDevs. 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. --

Downloads · 30 days

19% of all-time downloads

All-time downloads

Public

Repo size

3.1 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.3 GB · 98%

At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Jul 24, 2023
Updated: Jul 27, 2023
SHA: 03dbadf3

Datasets

common_voice

Model card

From the Hugging Face model README

wav2vec2-large-xls-r-300m-kinyarwanda

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 0.3917
Wer: 0.3246

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: 7e-05
train_batch_size: 12
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 24
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 400
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
9.0634	0.12	400	3.0554	1.0
2.8009	0.24	800	1.5927	0.9554
0.9022	0.36	1200	0.7328	0.6445
0.6213	0.48	1600	0.6138	0.5510
0.5299	0.6	2000	0.6072	0.5223
0.4999	0.72	2400	0.5449	0.4969
0.4731	0.84	2800	0.5261	0.4828
0.458	0.96	3200	0.5058	0.4607
0.4158	1.09	3600	0.4892	0.4463
0.4037	1.21	4000	0.4759	0.4429
0.4021	1.33	4400	0.4615	0.4330
0.3934	1.45	4800	0.4593	0.4315
0.3808	1.57	5200	0.4736	0.4344
0.3838	1.69	5600	0.4569	0.4249
0.3726	1.81	6000	0.4473	0.4140
0.3623	1.93	6400	0.4403	0.4097
0.3517	2.05	6800	0.4389	0.4061
0.333	2.17	7200	0.4383	0.4104
0.3354	2.29	7600	0.4360	0.3955
0.3257	2.41	8000	0.4226	0.3942
0.3275	2.53	8400	0.4206	0.4040
0.3262	2.65	8800	0.4172	0.3875
0.3206	2.77	9200	0.4209	0.3877
0.323	2.89	9600	0.4177	0.3825
0.3099	3.01	10000	0.4101	0.3691
0.3008	3.14	10400	0.4055	0.3709
0.2918	3.26	10800	0.4085	0.3800
0.292	3.38	11200	0.4089	0.3713
0.292	3.5	11600	0.4092	0.3730
0.2785	3.62	12000	0.4151	0.3687
0.2941	3.74	12400	0.4004	0.3639
0.2838	3.86	12800	0.4108	0.3703
0.2854	3.98	13200	0.3911	0.3596
0.2683	4.1	13600	0.3944	0.3575
0.2647	4.22	14000	0.3836	0.3538
0.2704	4.34	14400	0.4006	0.3540
0.2664	4.46	14800	0.3974	0.3553
0.2662	4.58	15200	0.3890	0.3470
0.2615	4.7	15600	0.3856	0.3507
0.2553	4.82	16000	0.3814	0.3497
0.2587	4.94	16400	0.3837	0.3440
0.2522	5.06	16800	0.3834	0.3486
0.2451	5.19	17200	0.3897	0.3414
0.2423	5.31	17600	0.3864	0.3481
0.2434	5.43	18000	0.3808	0.3416
0.2525	5.55	18400	0.3795	0.3408
0.2427	5.67	18800	0.3841	0.3411
0.2411	5.79	19200	0.3804	0.3366
0.2404	5.91	19600	0.3800	0.3328
0.2372	6.03	20000	0.3749	0.3335
0.2244	6.15	20400	0.3820	0.3327
0.2381	6.27	20800	0.3789	0.3325
0.2294	6.39	21200	0.3867	0.3298
0.2378	6.51	21600	0.3843	0.3281
0.2312	6.63	22000	0.3813	0.3277
0.2411	6.75	22400	0.3780	0.3268
0.2315	6.87	22800	0.3790	0.3280
0.241	6.99	23200	0.3776	0.3281
0.2313	7.11	23600	0.3929	0.3283
0.2423	7.24	24000	0.3905	0.3280
0.2337	7.36	24400	0.3979	0.3249
0.2368	7.48	24800	0.3980	0.3257
0.2409	7.6	25200	0.3937	0.3229
0.2416	7.72	25600	0.3867	0.3237
0.2364	7.84	26000	0.3912	0.3253
0.234	7.96	26400	0.3917	0.3246

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Jul 24, 2023
Updated: Jul 27, 2023