testing_pretrained_niger_mali

YassineBenlaria/testing_pretrained_niger_mali

testing_pretrained_niger_mali is a automatic speech recognition model from YassineBenlaria. Use it when you need speech turned into text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: wav2vec2
Access: Public
Created: Sep 22, 2023
Updated: Sep 22, 2023
SHA: 48c0b96f

Model card

From the Hugging Face model README

testing_pretrained_niger_mali

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.9245
Wer: 0.8889

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: 3e-05
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: 350

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.427	35.29	300	2.9588	1.0
2.8653	70.59	600	2.7466	1.0
2.7675	105.88	900	2.7207	1.0
2.6674	141.18	1200	2.2285	1.0
1.7813	176.47	1500	1.5717	0.8852
1.0447	211.76	1800	1.7009	0.8778
0.8167	247.06	2100	1.8010	0.8815
0.7059	282.35	2400	1.8748	0.8815
0.6572	317.65	2700	1.9245	0.8889

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Sep 22, 2023
Updated: Sep 22, 2023