whisper-small-hyper-tuned-v2 – AI Model by Sekiraw | AlphaNeural AI

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Sekiraw/
whisper-small-hyper-tuned-v2

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automatic-speech-recognition

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openai/whisper-small

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whisper-small-hyper-tuned-v2

This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2138
Wer: 0.3859

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: 5e-05
train_batch_size: 16
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: 500
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2719	0.0330	100	0.3551	0.5211
0.2793	0.0660	200	0.3262	0.4921
0.2831	0.0990	300	0.3306	0.4927
0.2775	0.1320	400	0.3631	0.5363
0.2849	0.1650	500	0.3488	0.5040
0.2692	0.1980	600	0.3202	0.4967
0.2528	0.2309	700	0.2838	0.4400
0.2155	0.2639	800	0.2489	0.4116
0.1929	0.2969	900	0.2220	0.3912
0.1709	0.3299	1000	0.2138	0.3859

Framework versions

Transformers 4.45.1
Pytorch 2.1.0+cu118
Datasets 3.0.1
Tokenizers 0.20.0