aradia-ctc-v1

abdusah/aradia-ctc-v1

aradia-ctc-v1 is a automatic speech recognition model from abdusah. Use it when you need speech turned into text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: wav2vec2
Access: Public
Created: Mar 23, 2022
Updated: Mar 30, 2022
SHA: ce169be1

Model card

From the Hugging Face model README

aradia-ctc-v1

This model is a fine-tuned version of /l/users/abdulwahab.sahyoun/aradia/aradia-ctc-v1 on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA dataset. It achieves the following results on the evaluation set:

Loss: 0.7171
Wer: 0.3336

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.22	100	5.1889	1.0
No log	0.43	200	3.1129	1.0
No log	0.65	300	3.0503	1.0
No log	0.87	400	3.0279	1.0
6.2756	1.09	500	2.9965	1.0
6.2756	1.3	600	2.3618	0.9993
6.2756	1.52	700	1.2715	0.8758
6.2756	1.74	800	0.9971	0.7156
6.2756	1.96	900	0.8927	0.6382
1.712	2.17	1000	0.8252	0.5926
1.712	2.39	1100	0.7794	0.5434
1.712	2.61	1200	0.7557	0.5092
1.712	2.83	1300	0.7347	0.5203
1.712	3.04	1400	0.7189	0.4929
0.9305	3.26	1500	0.6820	0.4595
0.9305	3.48	1600	0.6792	0.4504
0.9305	3.69	1700	0.6596	0.4442
0.9305	3.91	1800	0.6756	0.4432
0.9305	4.13	1900	0.6663	0.4392
0.737	4.35	2000	0.6479	0.4372
0.737	4.56	2100	0.6353	0.4203
0.737	4.78	2200	0.6251	0.4088
0.737	5.0	2300	0.6209	0.4177
0.737	5.22	2400	0.6639	0.4094
0.6247	5.43	2500	0.6408	0.3970
0.6247	5.65	2600	0.6373	0.3932
0.6247	5.87	2700	0.6411	0.3928
0.6247	6.09	2800	0.6378	0.3897
0.6247	6.3	2900	0.6396	0.3929
0.5443	6.52	3000	0.6544	0.3864
0.5443	6.74	3100	0.6218	0.3786
0.5443	6.96	3200	0.6200	0.3784
0.5443	7.17	3300	0.6157	0.3791
0.5443	7.39	3400	0.6317	0.3798
0.4845	7.61	3500	0.6540	0.3771
0.4845	7.83	3600	0.6436	0.3670
0.4845	8.04	3700	0.6335	0.3695
0.4845	8.26	3800	0.6579	0.3610
0.4845	8.48	3900	0.6170	0.3613
0.4279	8.69	4000	0.6523	0.3617
0.4279	8.91	4100	0.6349	0.3577
0.4279	9.13	4200	0.6344	0.3673
0.4279	9.35	4300	0.6215	0.3641
0.4279	9.56	4400	0.6513	0.3608
0.3825	9.78	4500	0.6386	0.3605
0.3825	10.0	4600	0.6724	0.3549
0.3825	10.22	4700	0.6776	0.3602
0.3825	10.43	4800	0.6739	0.3544
0.3825	10.65	4900	0.6688	0.3557
0.3477	10.87	5000	0.6674	0.3564
0.3477	11.09	5100	0.6786	0.3476
0.3477	11.3	5200	0.6818	0.3478
0.3477	11.52	5300	0.6874	0.3470
0.3477	11.74	5400	0.6993	0.3424
0.3101	11.96	5500	0.6950	0.3404
0.3101	12.17	5600	0.6872	0.3406
0.3101	12.39	5700	0.6846	0.3424
0.3101	12.61	5800	0.7051	0.3405
0.3101	12.83	5900	0.7051	0.3378
0.2859	13.04	6000	0.6955	0.3403
0.2859	13.26	6100	0.7115	0.3390
0.2859	13.48	6200	0.7074	0.3384
0.2859	13.69	6300	0.7002	0.3376
0.2859	13.91	6400	0.7171	0.3360
0.2714	14.13	6500	0.7193	0.3341
0.2714	14.35	6600	0.7132	0.3347
0.2714	14.56	6700	0.7184	0.3353
0.2714	14.78	6800	0.7171	0.3331

Framework versions

Transformers 4.18.0.dev0
Pytorch 1.10.2+cu113
Datasets 1.18.4
Tokenizers 0.11.6

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Mar 23, 2022
Updated: Mar 30, 2022