whisper_small_en_to_pf10h – AI Model by rishabhjain16 | AlphaNeural AI

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whisper_small_en_to_pf10h

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automatic-speech-recognition

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openai/whisper-small.en

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

Loss: 0.1764
Wer: 2.9777

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: 64
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
0.0179	10.0	500	0.1422	3.4691
0.0006	20.0	1000	0.1530	3.0001
0.0004	30.01	1500	0.1631	3.0150
0.0002	40.01	2000	0.1672	2.9777
0.0001	51.0	2500	0.1717	2.9703
0.0001	61.0	3000	0.1742	2.9926
0.0001	71.01	3500	0.1759	2.9852
0.0001	81.01	4000	0.1764	2.9777

Framework versions

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