finetuning-1-12-2022

ASR/finetuning-1-12-2022

finetuning-1-12-2022 is a automatic speech recognition model from ASR. 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: Dec 1, 2022
Updated: Dec 2, 2022
SHA: 34c5d9ee

Model card

From the Hugging Face model README

finetuning-1-12-2022

This model is a fine-tuned version of ASR/Finetuning on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0357
Wer: 0.0836

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	45	2.6669	1.0
No log	2.0	90	1.4650	0.9652
No log	3.0	135	0.8614	0.7491
No log	4.0	180	0.8031	0.7735
No log	5.0	225	0.7993	0.7909
No log	6.0	270	0.5708	0.6411
No log	7.0	315	0.5728	0.7178
No log	8.0	360	0.5439	0.6341
1.2911	9.0	405	0.5072	0.7213
1.2911	10.0	450	0.3578	0.5331
1.2911	11.0	495	0.4871	0.6411
1.2911	12.0	540	0.3034	0.4634
1.2911	13.0	585	0.4684	0.6028
1.2911	14.0	630	0.2638	0.4216
1.2911	15.0	675	0.2657	0.4948
1.2911	16.0	720	0.2593	0.3972
1.2911	17.0	765	0.2770	0.4634
0.3079	18.0	810	0.2936	0.4530
0.3079	19.0	855	0.4168	0.5436
0.3079	20.0	900	0.2642	0.3693
0.3079	21.0	945	0.1827	0.3519
0.3079	22.0	990	0.1807	0.2962
0.3079	23.0	1035	0.2134	0.3484
0.3079	24.0	1080	0.1317	0.2474
0.3079	25.0	1125	0.0950	0.2021
0.3079	26.0	1170	0.0985	0.1707
0.1678	27.0	1215	0.1444	0.2753
0.1678	28.0	1260	0.0816	0.1289
0.1678	29.0	1305	0.1103	0.1916
0.1678	30.0	1350	0.0878	0.1777
0.1678	31.0	1395	0.1436	0.1568
0.1678	32.0	1440	0.1097	0.1882
0.1678	33.0	1485	0.0995	0.1777
0.1678	34.0	1530	0.0917	0.1882
0.1678	35.0	1575	0.0691	0.1254
0.0743	36.0	1620	0.0394	0.0941
0.0743	37.0	1665	0.0592	0.1185
0.0743	38.0	1710	0.0680	0.1220
0.0743	39.0	1755	0.0748	0.0941
0.0743	40.0	1800	0.0651	0.1010
0.0743	41.0	1845	0.0688	0.1045
0.0743	42.0	1890	0.0489	0.0871
0.0743	43.0	1935	0.0524	0.0976
0.0743	44.0	1980	0.0415	0.1080
0.0234	45.0	2025	0.0489	0.0767
0.0234	46.0	2070	0.0337	0.0732
0.0234	47.0	2115	0.0456	0.0662
0.0234	48.0	2160	0.0326	0.0871
0.0234	49.0	2205	0.0319	0.0976
0.0234	50.0	2250	0.0357	0.0836

Framework versions

Transformers 4.23.0
Pytorch 1.13.0+cpu
Datasets 2.5.2
Tokenizers 0.13.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Dec 1, 2022
Updated: Dec 2, 2022