mst_hp5 – AI Model by Sjdan | AlphaNeural AI

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Sjdan/
mst_hp5

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automatic-speech-recognition

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mst_hp5

This model is a fine-tuned version of Sjdan/mst_1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0318
Wer: 1.3707

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: 4
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: 7
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.6474	0.68	500	0.9410	2.2056
0.861	1.36	1000	0.2756	1.7009
0.4965	2.04	1500	0.1673	1.8972
0.2657	2.72	2000	0.1216	1.8785
0.204	3.41	2500	0.0882	1.4424
0.1388	4.09	3000	0.0453	1.6636
0.1099	4.77	3500	0.0408	1.4953
0.0673	5.45	4000	0.0402	1.5452
0.0585	6.13	4500	0.0422	1.3863
0.036	6.81	5000	0.0318	1.3707

Framework versions

Transformers 4.17.0
Pytorch 1.13.1+cu116
Datasets 1.18.3
Tokenizers 0.13.2