Model_G_S_P_Wav2Vec2

rossevine/Model_G_S_P_Wav2Vec2

Model_G_S_P_Wav2Vec2 is a automatic speech recognition model from rossevine. 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: Aug 14, 2023
Updated: Sep 8, 2023
SHA: d0917de8

Model card

From the Hugging Face model README

Model_G_S_P_Wav2Vec2

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

Loss: 2.5098
Wer: 0.5366
Cer: 0.2277

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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.0449	3.49	400	1.7576	0.6270	0.2607
0.484	6.99	800	1.8072	0.6043	0.2536
0.3335	10.48	1200	2.0222	0.5892	0.2500
0.2559	13.97	1600	2.4174	0.5719	0.2448
0.1999	17.47	2000	2.2888	0.5566	0.2376
0.1546	20.96	2400	2.5271	0.5753	0.2400
0.1225	24.45	2800	2.4489	0.5427	0.2327
0.0983	27.95	3200	2.5098	0.5366	0.2277

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Aug 14, 2023
Updated: Sep 8, 2023