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peter2000/
wav2vec2-large-xls-r-300m-kinyarwanda

Name: wav2vec2-large-xls-r-300m-kinyarwanda
Availability: InStock

automatic-speech-recognition

generated_from_trainer

common_voice

apache-2.0

endpoints_compatible

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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

peter2000/wav2vec2-large-xls-r-300m-kinyarwanda

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

peter2000/
wav2vec2-large-xls-r-300m-kinyarwanda