wav2vec2-dataset-vios

tclong/wav2vec2-dataset-vios

wav2vec2-dataset-vios is a automatic speech recognition model from tclong. 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 29, 2022
Updated: May 30, 2022
SHA: 935c98b4

Datasets

vivos_dataset

Model card

From the Hugging Face model README

wav2vec2-dataset-vios

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the vivos_dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.5423
Wer: 0.4075

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.0963	1.1	400	1.1336	0.7374
0.6576	2.2	800	0.4716	0.3727
0.4099	3.3	1200	0.3907	0.3100
0.3332	4.4	1600	0.3735	0.2766
0.2976	5.49	2000	0.3932	0.2801
0.2645	6.59	2400	0.3628	0.2542
0.2395	7.69	2800	0.3702	0.2734
0.2208	8.79	3200	0.3667	0.2467
0.1974	9.89	3600	0.3688	0.2398
0.1772	10.99	4000	0.3819	0.2457
0.1695	12.09	4400	0.3840	0.2451
0.319	13.19	4800	0.6531	0.4084
0.7305	14.29	5200	0.9883	0.6348
0.5787	15.38	5600	0.5260	0.3063
0.8558	16.48	6000	1.2870	0.7692
1.155	17.58	6400	1.0568	0.6353
0.8393	18.68	6800	0.7360	0.4486
0.6094	19.78	7200	0.6072	0.4108
0.5346	20.88	7600	0.5749	0.4095
0.5073	21.98	8000	0.5588	0.4056
0.4859	23.08	8400	0.5475	0.4015
0.475	24.18	8800	0.5430	0.4011
0.4683	25.27	9200	0.5400	0.3990
0.4673	26.37	9600	0.5407	0.4011
0.4665	27.47	10000	0.5408	0.3992
0.4703	28.57	10400	0.5420	0.4070
0.4709	29.67	10800	0.5423	0.4075

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: May 29, 2022
Updated: May 30, 2022