whisper-small-vi-v1 – AI Model by shivkumarganesh | AlphaNeural AI

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whisper-small-vi-v1

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automatic-speech-recognition

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mozilla-foundation/common_voice_11_0

endpoints_compatible

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Whisper Medium Vi v1 - Shiv Kumar Ganesh

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 1.0641
Wer: 34.0974

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: 32
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: 500
training_steps: 7000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0005	31.0	500	0.7179	33.7464
0.0002	62.0	1000	0.7837	32.4742
0.0001	93.0	1500	0.8267	34.2729
0.0001	124.0	2000	0.8677	35.1722
0.0	156.0	2500	0.9045	35.3257
0.0	187.0	3000	0.9316	33.9877
0.0	218.0	3500	0.9585	34.0097
0.0	249.0	4000	0.9846	33.3626
0.0	281.0	4500	1.0082	33.4832
0.0	312.0	5000	1.0247	33.7026
0.0	343.0	5500	1.0391	32.8691
0.0	374.0	6000	1.0516	32.9020
0.0	406.0	6500	1.0606	33.6477
0.0	437.0	7000	1.0641	34.0974

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.1.dev0
Tokenizers 0.13.2