aradia-ctc-distilhubert-ft

abdusah/aradia-ctc-distilhubert-ft

aradia-ctc-distilhubert-ft is a automatic speech recognition model from abdusah. 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

2% of all-time downloads

All-time downloads

562

Public

Repo size

1.8 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin94.2 MB · 100%

At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: hubert
Access: Public
Created: Apr 6, 2022
Updated: Apr 7, 2022
SHA: 20e8824d

Model card

From the Hugging Face model README

aradia-ctc-distilhubert-ft

This model is a fine-tuned version of ntu-spml/distilhubert on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_SM - NA dataset. It achieves the following results on the evaluation set:

Loss: 2.7114
Wer: 0.8908

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: 30.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.43	100	4.4129	1.0
No log	0.87	200	3.5927	1.0
No log	1.3	300	3.3780	1.0
No log	1.74	400	3.0830	1.0
5.3551	2.17	500	2.6278	0.9999
5.3551	2.61	600	1.8359	1.0000
5.3551	3.04	700	1.7878	0.9914
5.3551	3.48	800	1.5219	0.9875
5.3551	3.91	900	1.4348	0.9879
1.7199	4.35	1000	1.4354	0.9644
1.7199	4.78	1100	1.5210	0.9519
1.7199	5.22	1200	1.3607	0.9475
1.7199	5.65	1300	1.3839	0.9343
1.7199	6.09	1400	1.2806	0.8944
1.2342	6.52	1500	1.3036	0.9011
1.2342	6.95	1600	1.3704	0.9072
1.2342	7.39	1700	1.2981	0.8891
1.2342	7.82	1800	1.2786	0.8733
1.2342	8.26	1900	1.2897	0.8867
0.9831	8.69	2000	1.4436	0.8780
0.9831	9.13	2100	1.3680	0.8873
0.9831	9.56	2200	1.3471	0.8692
0.9831	10.0	2300	1.3725	0.8729
0.9831	10.43	2400	1.4439	0.8771
0.8071	10.87	2500	1.5114	0.8928
0.8071	11.3	2600	1.6156	0.8958
0.8071	11.74	2700	1.4381	0.8749
0.8071	12.17	2800	1.5088	0.8717
0.8071	12.61	2900	1.5486	0.8813
0.6321	13.04	3000	1.4536	0.8884
0.6321	13.48	3100	1.4679	0.8947
0.6321	13.91	3200	1.5628	0.9117
0.6321	14.35	3300	1.5831	0.8716
0.6321	14.78	3400	1.6733	0.8702
0.4998	15.22	3500	1.8225	0.8665
0.4998	15.65	3600	1.8558	0.8732
0.4998	16.09	3700	1.7513	0.8766
0.4998	16.52	3800	1.8562	0.8753
0.4998	16.95	3900	1.9018	0.8704
0.4421	17.39	4000	1.9341	0.8789
0.4421	17.82	4100	1.9582	0.8781
0.4421	18.26	4200	1.8863	0.8821
0.4421	18.69	4300	1.9366	0.8847
0.4421	19.13	4400	2.1902	0.8721
0.3712	19.56	4500	2.1641	0.8670
0.3712	20.0	4600	2.1639	0.8776
0.3712	20.43	4700	2.2695	0.9030
0.3712	20.87	4800	2.1909	0.8937
0.3712	21.3	4900	2.1606	0.8959
0.3067	21.74	5000	2.1756	0.8943
0.3067	22.17	5100	2.4092	0.8773
0.3067	22.61	5200	2.4991	0.8721
0.3067	23.04	5300	2.3340	0.8910
0.3067	23.48	5400	2.3567	0.8946
0.2764	23.91	5500	2.3215	0.8897
0.2764	24.35	5600	2.4824	0.9002
0.2764	24.78	5700	2.4585	0.8963
0.2764	25.22	5800	2.5804	0.8879
0.2764	25.65	5900	2.5814	0.8903
0.2593	26.09	6000	2.5374	0.8868
0.2593	26.52	6100	2.5346	0.8922
0.2593	26.95	6200	2.5465	0.8873
0.2593	27.39	6300	2.6002	0.8919
0.2593	27.82	6400	2.6102	0.8928
0.227	28.26	6500	2.6925	0.8914
0.227	28.69	6600	2.6981	0.8913
0.227	29.13	6700	2.6872	0.8891
0.227	29.56	6800	2.7015	0.8897
0.227	30.0	6900	2.7114	0.8908

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: hubert
License: apache-2.0
Created: Apr 6, 2022
Updated: Apr 7, 2022