xls-asr-vi-40h

geninhu/xls-asr-vi-40h

xls-asr-vi-40h is a automatic speech recognition model from geninhu. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common voice 7.0 vi & private dataset. It achieves the following results on the evaluation set (Without Language Model): - Loss: 1.1177 - Wer:…

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Mar 2, 2022
Updated: Mar 23, 2022
SHA: 34f61a54

Datasets

mozilla-foundation/common_voice_7_0

Model card

From the Hugging Face model README

xls-asr-vi-40h

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common voice 7.0 vi & private dataset. It achieves the following results on the evaluation set (Without Language Model):

Loss: 1.1177
Wer: 60.58

Evaluation

Please run the eval.py file

!python eval_custom.py --model_id geninhu/xls-asr-vi-40h --dataset mozilla-foundation/common_voice_7_0 --config vi --split test

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1500
num_epochs: 50.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
23.3878	0.93	1500	21.9179	1.0
8.8862	1.85	3000	6.0599	1.0
4.3701	2.78	4500	4.3837	1.0
4.113	3.7	6000	4.2698	0.9982
3.9666	4.63	7500	3.9726	0.9989
3.5965	5.56	9000	3.7124	0.9975
3.3944	6.48	10500	3.5005	1.0057
3.304	7.41	12000	3.3710	1.0043
3.2482	8.33	13500	3.4201	1.0155
3.212	9.26	15000	3.3732	1.0151
3.1778	10.19	16500	3.2763	1.0009
3.1027	11.11	18000	3.1943	1.0025
2.9905	12.04	19500	2.8082	0.9703
2.7095	12.96	21000	2.4993	0.9302
2.4862	13.89	22500	2.3072	0.9140
2.3271	14.81	24000	2.1398	0.8949
2.1968	15.74	25500	2.0594	0.8817
2.111	16.67	27000	1.9404	0.8630
2.0387	17.59	28500	1.8895	0.8497
1.9504	18.52	30000	1.7961	0.8315
1.9039	19.44	31500	1.7433	0.8213
1.8342	20.37	33000	1.6790	0.7994
1.7824	21.3	34500	1.6291	0.7825
1.7359	22.22	36000	1.5783	0.7706
1.7053	23.15	37500	1.5248	0.7492
1.6504	24.07	39000	1.4930	0.7406
1.6263	25.0	40500	1.4572	0.7348
1.5893	25.93	42000	1.4202	0.7161
1.5669	26.85	43500	1.3987	0.7143
1.5277	27.78	45000	1.3512	0.6991
1.501	28.7	46500	1.3320	0.6879
1.4781	29.63	48000	1.3112	0.6788
1.4477	30.56	49500	1.2850	0.6657
1.4483	31.48	51000	1.2813	0.6633
1.4065	32.41	52500	1.2475	0.6541
1.3779	33.33	54000	1.2244	0.6503
1.3788	34.26	55500	1.2116	0.6407
1.3428	35.19	57000	1.1938	0.6352
1.3453	36.11	58500	1.1927	0.6340
1.3137	37.04	60000	1.1699	0.6252
1.2984	37.96	61500	1.1666	0.6229
1.2927	38.89	63000	1.1585	0.6188
1.2919	39.81	64500	1.1618	0.6190
1.293	40.74	66000	1.1479	0.6181
1.2853	41.67	67500	1.1423	0.6202
1.2687	42.59	69000	1.1315	0.6131
1.2603	43.52	70500	1.1333	0.6128
1.2577	44.44	72000	1.1191	0.6079
1.2435	45.37	73500	1.1177	0.6079
1.251	46.3	75000	1.1211	0.6092
1.2482	47.22	76500	1.1177	0.6060
1.2422	48.15	78000	1.1227	0.6097
1.2485	49.07	79500	1.1187	0.6071
1.2425	50.0	81000	1.1177	0.6058

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.11.0

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Languages: vi
Created: Mar 2, 2022
Updated: Mar 23, 2022