whisper_medium_to_pf10h – AI Model by rishabhjain16 | AlphaNeural AI

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whisper_medium_to_pf10h

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automatic-speech-recognition

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openai/whisper-medium

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

Loss: 0.1594
Wer: 21.8343

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: 32
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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0269	5.0	500	0.1069	118.0302
0.0049	10.01	1000	0.1263	135.2788
0.0009	15.01	1500	0.1355	94.5731
0.0001	20.01	2000	0.1413	7.5188
0.0001	25.01	2500	0.1515	7.2508
0.0001	30.02	3000	0.1568	24.8493
0.0	35.02	3500	0.1588	22.1470
0.0	40.02	4000	0.1594	21.8343

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.9.1.dev0
Tokenizers 0.13.2