Echotune_clean_test

jjyaoao/Echotune_clean_test

Echotune_clean_test is a automatic speech recognition model from jjyaoao. 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: data2vec-audio
Access: Public
Created: Aug 7, 2023
Updated: Aug 23, 2023
SHA: 57b9437c

Base models

facebook/data2vec-audio-base-960h

Datasets

librispeech_asr

Model card

From the Hugging Face model README

jjyaoao/Echotune_clean_test

This model is a fine-tuned version of facebook/data2vec-audio-base-960h on the librispeech_asr dataset. It achieves the following results on the evaluation set:

Loss: 0.0679
Wer Ortho: 0.0369
Wer: 0.0374

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: 6e-05
train_batch_size: 12
eval_batch_size: 12
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 34246.8
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0602	0.21	500	0.0476	0.0435	0.0439
0.0478	0.42	1000	0.0436	0.0411	0.0414
0.0492	0.63	1500	0.0443	0.0412	0.0415
0.0426	0.84	2000	0.0439	0.0401	0.0403
0.0386	1.05	2500	0.0445	0.0391	0.0395
0.0409	1.26	3000	0.0438	0.0394	0.0399
0.0437	1.47	3500	0.0444	0.0389	0.0393
0.0349	1.68	4000	0.0450	0.0392	0.0396
0.0469	1.89	4500	0.0442	0.0374	0.0378
0.033	2.1	5000	0.0454	0.0359	0.0363
0.0395	2.31	5500	0.0462	0.0363	0.0367
0.0321	2.52	6000	0.0457	0.0365	0.0369
0.0385	2.73	6500	0.0455	0.0355	0.0358
0.0378	2.94	7000	0.0449	0.0361	0.0366
0.0435	3.15	7500	0.0440	0.0355	0.0360
0.0436	3.36	8000	0.0466	0.0339	0.0344
0.0394	3.57	8500	0.0480	0.0345	0.0350
0.0448	3.78	9000	0.0478	0.0338	0.0342
0.0451	3.99	9500	0.0460	0.0355	0.0361
0.035	4.2	10000	0.0485	0.0369	0.0374
0.0387	4.41	10500	0.0487	0.0358	0.0362
0.0479	4.62	11000	0.0496	0.0363	0.0368
0.0456	4.83	11500	0.0491	0.0359	0.0365
0.0372	5.04	12000	0.0507	0.0355	0.0360
0.0395	5.25	12500	0.0526	0.0353	0.0356
0.0323	5.46	13000	0.0515	0.0368	0.0373
0.0354	5.67	13500	0.0524	0.0338	0.0343
0.031	5.88	14000	0.0531	0.0349	0.0357
0.0295	6.09	14500	0.0560	0.0344	0.0349
0.032	6.31	15000	0.0564	0.0364	0.0369
0.0462	6.52	15500	0.0548	0.0358	0.0365
0.0467	6.73	16000	0.0562	0.0347	0.0352
0.0437	6.94	16500	0.0573	0.0354	0.0359
0.0357	7.15	17000	0.0561	0.0359	0.0362
0.0297	7.36	17500	0.0602	0.0347	0.0351
0.0388	7.57	18000	0.0552	0.0341	0.0345
0.0392	7.78	18500	0.0533	0.0326	0.0331
0.0419	7.99	19000	0.0535	0.0343	0.0349
0.0326	8.2	19500	0.0614	0.0374	0.0378
0.0423	8.41	20000	0.0585	0.0341	0.0346
0.0326	8.62	20500	0.0586	0.0356	0.0362
0.0448	8.83	21000	0.0637	0.0371	0.0375
0.0763	9.04	21500	0.0607	0.0359	0.0364
0.0317	9.25	22000	0.0635	0.0400	0.0405
0.0326	9.46	22500	0.0603	0.0368	0.0372
0.0393	9.67	23000	0.0665	0.0380	0.0385
0.0341	9.88	23500	0.0664	0.0408	0.0413
0.0351	10.09	24000	0.0638	0.0384	0.0388
0.0412	10.3	24500	0.0687	0.0380	0.0384
0.0359	10.51	25000	0.0634	0.0379	0.0385
0.047	10.72	25500	0.0652	0.0373	0.0378
0.0346	10.93	26000	0.0671	0.0390	0.0396
0.0366	11.14	26500	0.0664	0.0387	0.0393
0.0359	11.35	27000	0.0669	0.0369	0.0374
0.0366	11.56	27500	0.0705	0.0358	0.0364
0.054	11.77	28000	0.0659	0.0383	0.0390
0.0335	11.98	28500	0.0679	0.0369	0.0374

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.0+cu117
Datasets 2.13.1
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: data2vec-audio
License: apache-2.0
Created: Aug 7, 2023
Updated: Aug 23, 2023