wav2vec2-custom-colab

GW12/wav2vec2-custom-colab

wav2vec2-custom-colab is a automatic speech recognition model from GW12. 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: Feb 3, 2023
Updated: Feb 6, 2023
SHA: c1259091

Model card

From the Hugging Face model README

wav2vec2-custom-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: 0.7785
Wer: 0.3534

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: 1
eval_batch_size: 1
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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4783	0.3	500	0.7199	0.5564
0.4833	0.61	1000	0.8089	0.6181
0.5733	0.91	1500	0.7617	0.5530
0.4641	1.21	2000	0.7937	0.5731
0.4167	1.52	2500	0.7993	0.5102
0.3713	1.82	3000	0.7541	0.5437
0.3395	2.12	3500	0.7658	0.5148
0.2814	2.42	4000	0.7569	0.4783
0.2698	2.73	4500	0.8126	0.5174
0.2767	3.03	5000	0.7838	0.4676
0.2249	3.33	5500	0.8769	0.4743
0.2452	3.64	6000	0.8586	0.4778
0.1828	3.94	6500	0.7695	0.4528
0.1901	4.24	7000	0.7800	0.5021
0.2062	4.55	7500	0.8107	0.4567
0.1614	4.85	8000	0.7941	0.4094
0.1327	5.15	8500	0.7900	0.4241
0.1405	5.45	9000	0.8017	0.3992
0.1219	5.76	9500	0.8099	0.4043
0.1406	6.06	10000	0.8731	0.3913
0.0806	6.36	10500	0.8387	0.3868
0.1039	6.67	11000	0.8105	0.3905
0.0967	6.97	11500	0.7291	0.3728
0.0846	7.27	12000	0.8128	0.4201
0.0722	7.58	12500	0.8204	0.3751
0.0785	7.88	13000	0.7692	0.3760
0.0647	8.18	13500	0.8294	0.3752
0.0523	8.48	14000	0.7646	0.3763
0.0623	8.79	14500	0.7773	0.3572
0.0477	9.09	15000	0.7379	0.3635
0.064	9.39	15500	0.7544	0.3538
0.0321	9.7	16000	0.8118	0.3557
0.0541	10.0	16500	0.7785	0.3534

Framework versions

Transformers 4.26.0
Pytorch 1.10.0
Datasets 2.9.0
Tokenizers 0.13.2

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Feb 3, 2023
Updated: Feb 6, 2023