888aatt – AI Model by joohwan | AlphaNeural AI

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888aatt

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888aatt

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

Loss: 0.0831
Wer: 44.8577

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: 8
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0732	0.18	500	0.2005	31.2302
0.048	0.36	1000	0.1672	20.4939
0.0624	0.54	1500	0.1348	50.5496
0.0797	0.72	2000	0.1061	33.1727
0.0551	0.9	2500	0.0894	37.4191
0.0144	1.08	3000	0.0831	44.8577

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3