wav2vec2-base-timit-demo-google-colab

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

wav2vec2-base-timit-demo-google-colab is a automatic speech recognition model from ones. 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: Jun 29, 2022
Updated: Jun 30, 2022
SHA: 7103a7a2

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: 0.5112
Wer: 0.9988

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
3.5557	1.0	500	1.6786	1.0
0.8407	2.01	1000	0.5356	0.9988
0.4297	3.01	1500	0.4431	0.9988
0.2989	4.02	2000	0.4191	0.9988
0.2338	5.02	2500	0.4251	0.9988
0.1993	6.02	3000	0.4618	0.9988
0.1585	7.03	3500	0.4577	0.9988
0.1386	8.03	4000	0.4099	0.9982
0.1234	9.04	4500	0.4945	0.9988
0.1162	10.04	5000	0.4597	0.9988
0.1008	11.04	5500	0.4563	0.9988
0.0894	12.05	6000	0.5157	0.9988
0.083	13.05	6500	0.5027	0.9988
0.0735	14.06	7000	0.4905	0.9994
0.0686	15.06	7500	0.4552	0.9988
0.0632	16.06	8000	0.5522	0.9988
0.061	17.07	8500	0.4874	0.9988
0.0626	18.07	9000	0.5243	0.9988
0.0475	19.08	9500	0.4798	0.9988
0.0447	20.08	10000	0.5250	0.9988
0.0432	21.08	10500	0.5195	0.9988
0.0358	22.09	11000	0.5008	0.9988
0.0319	23.09	11500	0.5376	0.9988
0.0334	24.1	12000	0.5149	0.9988
0.0269	25.1	12500	0.4911	0.9988
0.0275	26.1	13000	0.4907	0.9988
0.027	27.11	13500	0.4992	0.9988
0.0239	28.11	14000	0.5021	0.9988
0.0233	29.12	14500	0.5112	0.9988

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: Jun 29, 2022
Updated: Jun 30, 2022