whisper-small-Seneca – AI Model by RobbieJimersonJr | AlphaNeural AI

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whisper-small-Seneca

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Whisper Small Seneca

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

Loss: 0.5983
Wer: 27.4983

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: 2
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 7768
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1151	3.01	1000	0.4013	31.8326
0.0185	6.02	2000	0.4796	30.1660
0.0062	9.03	3000	0.5143	30.0417
0.0022	12.04	4000	0.5469	28.6301
0.0004	16.01	5000	0.5695	27.9522
0.0001	19.01	6000	0.5891	27.5294
0.0002	22.02	7000	0.5983	27.4983

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2