wav2vec2-demo-M01

yip-i/wav2vec2-demo-M01

wav2vec2-demo-M01 is a automatic speech recognition model from yip-i. 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: Nov 12, 2022
Updated: Nov 20, 2022
SHA: 51d04de5

Model card

From the Hugging Face model README

wav2vec2-demo-M01

This model is a fine-tuned version of yip-i/uaspeech-pretrained on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.7099
Wer: 1.4021

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
7.3895	0.9	500	2.9817	1.0007
3.0164	1.8	1000	2.9513	1.2954
3.0307	2.7	1500	2.8709	1.3286
3.1314	3.6	2000	2.8754	1.0
3.0395	4.5	2500	2.9289	1.0
3.2647	5.41	3000	2.8134	1.0014
2.9821	6.31	3500	2.8370	1.3901
2.9262	7.21	4000	2.8731	1.3809
2.9982	8.11	4500	4.4794	1.3958
3.0807	9.01	5000	2.8268	1.3951
2.8873	9.91	5500	2.8014	1.5336
2.8755	10.81	6000	2.8010	1.3873
3.2618	11.71	6500	3.1033	1.3463
3.0063	12.61	7000	2.7906	1.3753
2.8481	13.51	7500	2.7874	1.3837
2.876	14.41	8000	2.8239	1.0636
2.8966	15.32	8500	2.7753	1.3915
2.8839	16.22	9000	2.7874	1.3223
2.8351	17.12	9500	2.7755	1.3915
2.8185	18.02	10000	2.7600	1.3908
2.8193	18.92	10500	2.7542	1.3915
2.8023	19.82	11000	2.7528	1.3915
2.7934	20.72	11500	2.7406	1.3915
2.8043	21.62	12000	2.7419	1.3915
2.7941	22.52	12500	2.7407	1.3915
2.7854	23.42	13000	2.7277	1.3915
2.7924	24.32	13500	2.7279	1.3915
2.7644	25.23	14000	2.7217	1.3915
2.7703	26.13	14500	2.7273	1.5032
2.7821	27.03	15000	2.7265	1.3915
2.7632	27.93	15500	2.7154	1.3915
2.749	28.83	16000	2.7125	1.3958
2.7515	29.73	16500	2.7099	1.4021

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 1.18.3
Tokenizers 0.13.2

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Nov 12, 2022
Updated: Nov 20, 2022