wav2vec2-large-xlsr-53_train_data_full

scasutt/wav2vec2-large-xlsr-53_train_data_full

wav2vec2-large-xlsr-53_train_data_full is a automatic speech recognition model from scasutt. 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. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

163

Public

Repo size

35.3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.3 GB · 100%

At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Apr 15, 2022
Updated: Apr 16, 2022
SHA: a8484980

Model card

From the Hugging Face model README

wav2vec2-large-xlsr-53_train_data_full

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4168
Wer: 0.3383

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: 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: 1000
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.0459	0.73	500	3.2037	0.9995
0.7938	1.45	1000	0.7432	0.6373
0.503	2.18	1500	0.5517	0.5115
0.4475	2.91	2000	0.4916	0.4624
0.3575	3.63	2500	0.4612	0.4362
0.3206	4.36	3000	0.4546	0.4198
0.3155	5.09	3500	0.4073	0.3929
0.2827	5.81	4000	0.4172	0.3808
0.2575	6.54	4500	0.4183	0.3741
0.2399	7.27	5000	0.4181	0.3680
0.2455	7.99	5500	0.3981	0.3604
0.2512	8.72	6000	0.4203	0.3612
0.221	9.45	6500	0.4073	0.3560
0.19	10.17	7000	0.4206	0.3547
0.207	10.9	7500	0.3992	0.3517
0.187	11.63	8000	0.4078	0.3517
0.2029	12.35	8500	0.4143	0.3469
0.171	13.08	9000	0.4007	0.3430
0.1658	13.81	9500	0.3862	0.3422
0.2021	14.53	10000	0.4132	0.3454
0.165	15.26	10500	0.3997	0.3407
0.1562	15.99	11000	0.4069	0.3416
0.1613	16.71	11500	0.4040	0.3393
0.1713	17.44	12000	0.4094	0.3411
0.1541	18.17	12500	0.4043	0.3367
0.144	18.89	13000	0.4086	0.3374
0.1483	19.62	13500	0.4168	0.3383

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu102
Datasets 2.1.0
Tokenizers 0.12.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Apr 15, 2022
Updated: Apr 16, 2022