w2v-bert-cv-grain-lg_both_v2

sulaimank/w2v-bert-cv-grain-lg_both_v2

w2v-bert-cv-grain-lg_both_v2 is a automatic speech recognition model from sulaimank. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: mit
Model type: wav2vec2-bert
Access: Public
Created: Nov 2, 2024
Updated: Nov 4, 2024
SHA: 4228eecc

Base models

facebook/w2v-bert-2.0

Model card

From the Hugging Face model README

w2v-bert-cv-grain-lg_both_v2

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0892
Wer: 0.0443
Cer: 0.0123

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: 4
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 80
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.2889	1.0	10812	0.1708	0.1703	0.0386
0.1849	2.0	21624	0.1342	0.1274	0.0285
0.1512	3.0	32436	0.1144	0.1044	0.0244
0.1313	4.0	43248	0.1033	0.0918	0.0217
0.117	5.0	54060	0.1034	0.0738	0.0191
0.1056	6.0	64872	0.0906	0.0738	0.0181
0.0962	7.0	75684	0.0959	0.0655	0.0168
0.0885	8.0	86496	0.0860	0.0592	0.0155
0.0807	9.0	97308	0.0844	0.0603	0.0154
0.0742	10.0	108120	0.0814	0.0573	0.0144
0.0683	11.0	118932	0.0858	0.0588	0.0154
0.0629	12.0	129744	0.0944	0.0538	0.0146
0.0581	13.0	140556	0.0842	0.0558	0.0151
0.0528	14.0	151368	0.0873	0.0503	0.0141
0.0479	15.0	162180	0.0820	0.0503	0.0138
0.0429	16.0	172992	0.0815	0.0427	0.0125
0.0392	17.0	183804	0.0864	0.0466	0.0128
0.035	18.0	194616	0.0899	0.0479	0.0128
0.0316	19.0	205428	0.0872	0.0430	0.0120
0.0286	20.0	216240	0.0821	0.0425	0.0114
0.0254	21.0	227052	0.0898	0.0466	0.0122
0.0229	22.0	237864	0.0864	0.0417	0.0120
0.021	23.0	248676	0.0893	0.0408	0.0122
0.0192	24.0	259488	0.0878	0.0430	0.0118
0.0171	25.0	270300	0.0994	0.0473	0.0128
0.0156	26.0	281112	0.0892	0.0443	0.0123

Framework versions

Transformers 4.46.1
Pytorch 2.1.0+cu118
Datasets 3.1.0
Tokenizers 0.20.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2-bert
License: mit
Created: Nov 2, 2024
Updated: Nov 4, 2024