wav2vec2-base-timit-demo-google-colab

zoha/wav2vec2-base-timit-demo-google-colab

wav2vec2-base-timit-demo-google-colab is a automatic speech recognition model from zoha. 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: wav2vec2
Access: Public
Created: May 18, 2022
Updated: Jun 13, 2022
SHA: 4eef48a4

Model card

From the Hugging Face model README

wav2vec2-base-timit-demo-google-colab

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5035
Wer: 0.3346

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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1411	1.0	500	0.6675	0.6001
0.5668	2.01	1000	0.4699	0.4973
0.3773	3.01	1500	0.4475	0.4403
0.2696	4.02	2000	0.4162	0.4166
0.2165	5.02	2500	0.3809	0.4011
0.1849	6.02	3000	0.4120	0.3849
0.1542	7.03	3500	0.4436	0.3770
0.1385	8.03	4000	0.3977	0.3732
0.1224	9.04	4500	0.4530	0.3672
0.1233	10.04	5000	0.3949	0.3596
0.1078	11.04	5500	0.4616	0.3539
0.097	12.05	6000	0.4354	0.3697
0.0821	13.05	6500	0.4370	0.3643
0.0724	14.06	7000	0.4729	0.3587
0.0678	15.06	7500	0.5822	0.3742
0.0632	16.06	8000	0.4460	0.3513
0.0627	17.07	8500	0.5531	0.3537
0.0574	18.07	9000	0.5262	0.3575
0.0515	19.08	9500	0.4794	0.3488
0.0475	20.08	10000	0.4941	0.3458
0.0463	21.08	10500	0.4741	0.3377
0.0392	22.09	11000	0.5390	0.3381
0.0401	23.09	11500	0.4984	0.3413
0.0371	24.1	12000	0.5112	0.3460
0.0305	25.1	12500	0.5255	0.3418
0.0278	26.1	13000	0.5045	0.3389
0.0265	27.11	13500	0.4990	0.3371
0.0248	28.11	14000	0.5242	0.3362
0.0249	29.12	14500	0.5035	0.3346

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 1.18.3
Tokenizers 0.12.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: May 18, 2022
Updated: Jun 13, 2022