swahili

etonkou/swahili

swahili is a automatic speech recognition model from etonkou. 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: Sep 29, 2023
Updated: Sep 29, 2023
SHA: ab73dabe

Base models

facebook/wav2vec2-base

Model card

From the Hugging Face model README

swahili

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: 1.0009
Wer: 0.6055

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: 3
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.723	1.5	1000	1.1521	0.7429
0.8457	3.0	2000	1.2019	0.7280
0.6465	4.5	3000	1.0385	0.6602
0.5081	6.0	4000	0.9303	0.6310
0.3864	7.5	5000	1.0838	0.6240
0.3109	9.0	6000	1.0009	0.6055

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Sep 29, 2023
Updated: Sep 29, 2023