preon-whisper-tiny-trial-4 – AI Model by gokulraj | AlphaNeural AI

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gokulraj/
preon-whisper-tiny-trial-4

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automatic-speech-recognition

generated_from_trainer

tamilcustomvoice

openai/whisper-medium

endpoints_compatible

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Whisper tiny custom

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

Loss: 0.0315
Wer Ortho: 9.2105
Wer: 7.2848

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
1.6536	2.5	50	0.4681	57.8947	50.9934
0.0732	5.0	100	0.0820	19.7368	15.2318
0.0076	7.5	150	0.0396	9.2105	7.9470
0.0013	10.0	200	0.0336	9.2105	8.6093
0.0007	12.5	250	0.0356	7.8947	5.9603
0.0005	15.0	300	0.0339	7.8947	5.9603
0.0004	17.5	350	0.0326	7.8947	5.9603
0.0003	20.0	400	0.0323	7.8947	5.9603
0.0003	22.5	450	0.0320	9.2105	7.2848
0.0002	25.0	500	0.0315	9.2105	7.2848

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1