Check_Model_1 – AI Model by rossevine | AlphaNeural AI | AlphaNeural AI

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Check_Model_1

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-large

endpoints_compatible

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Check_Model_1

This model is a fine-tuned version of facebook/wav2vec2-large on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 0.5522
Wer: 0.3748
Cer: 0.1158

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
2.1839	3.23	400	0.8796	0.7306	0.2332
0.6388	6.45	800	0.8702	0.6410	0.2200
0.4695	9.68	1200	0.7064	0.5360	0.1632
0.3659	12.9	1600	0.5814	0.5211	0.1662
0.285	16.13	2000	0.6394	0.5041	0.1663
0.2254	19.35	2400	0.5889	0.4428	0.1405
0.1801	22.58	2800	0.5712	0.4013	0.1182
0.1392	25.81	3200	0.5914	0.3934	0.1177
0.1051	29.03	3600	0.5522	0.3748	0.1158

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 1.18.3
Tokenizers 0.13.3