x-r-hy

yerevann/x-r-hy

x-r-hy is a automatic speech recognition model from yerevann. 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: Mar 2, 2022
Updated: Dec 19, 2021
SHA: dcf85100

Datasets

common_voice

Model card

From the Hugging Face model README

wav2vec2-large-xls-r-2b-armenian-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-2b on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 1.5166
Wer: 0.7397

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: 0.0001
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 120
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.7057	2.38	200	0.7731	0.8091
0.5797	4.76	400	0.8279	0.7804
0.4341	7.14	600	1.0343	0.8285
0.3135	9.52	800	1.0551	0.8066
0.2409	11.9	1000	1.0686	0.7897
0.1998	14.29	1200	1.1329	0.7766
0.1729	16.67	1400	1.3234	0.8567
0.1533	19.05	1600	1.2432	0.8160
0.1354	21.43	1800	1.2780	0.7954
0.12	23.81	2000	1.2228	0.8054
0.1175	26.19	2200	1.3484	0.8129
0.1141	28.57	2400	1.2881	0.9130
0.1053	30.95	2600	1.1972	0.7910
0.0954	33.33	2800	1.3702	0.8048
0.0842	35.71	3000	1.3963	0.7960
0.0793	38.1	3200	1.4690	0.7991
0.0707	40.48	3400	1.5045	0.8085
0.0745	42.86	3600	1.4749	0.8004
0.0693	45.24	3800	1.5047	0.7960
0.0646	47.62	4000	1.4216	0.7997
0.0555	50.0	4200	1.4676	0.8029
0.056	52.38	4400	1.4273	0.8104
0.0465	54.76	4600	1.3999	0.7841
0.046	57.14	4800	1.6130	0.8473
0.0404	59.52	5000	1.5586	0.7841
0.0403	61.9	5200	1.3959	0.7653
0.0404	64.29	5400	1.5318	0.8041
0.0365	66.67	5600	1.5300	0.7854
0.0338	69.05	5800	1.5051	0.7885
0.0307	71.43	6000	1.5647	0.7935
0.0235	73.81	6200	1.4919	0.8154
0.0268	76.19	6400	1.5259	0.8060
0.0275	78.57	6600	1.3985	0.7897
0.022	80.95	6800	1.5515	0.8154
0.017	83.33	7000	1.5737	0.7647
0.0205	85.71	7200	1.4876	0.7572
0.0174	88.1	7400	1.6331	0.7829
0.0188	90.48	7600	1.5108	0.7685
0.0134	92.86	7800	1.7125	0.7866
0.0125	95.24	8000	1.6042	0.7635
0.0133	97.62	8200	1.4608	0.7478
0.0272	100.0	8400	1.4784	0.7309
0.0133	102.38	8600	1.4471	0.7459
0.0094	104.76	8800	1.4852	0.7272
0.0103	107.14	9000	1.5679	0.7409
0.0088	109.52	9200	1.5090	0.7309
0.0077	111.9	9400	1.4994	0.7290
0.0068	114.29	9600	1.5008	0.7340
0.0054	116.67	9800	1.5166	0.7390
0.0052	119.05	10000	1.5166	0.7397

Framework versions

Transformers 4.14.1
Pytorch 1.10.0
Datasets 1.16.1
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Mar 2, 2022
Updated: Dec 19, 2021