whisper-tiny-en – AI Model by lfurman | AlphaNeural AI

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lfurman/
whisper-tiny-en

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automatic-speech-recognition

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openai/whisper-tiny

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Whisper Tiny En - FreeSound based captions

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

Loss: 5.5085
Wer: 91.7867

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: 8
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
0.8757	24.3902	1000	4.1235	97.8963
0.0518	48.7805	2000	4.8741	94.9280
0.0234	73.1707	3000	5.1544	93.1124
0.0148	97.5610	4000	5.3503	93.4294
0.0141	121.9512	5000	5.4099	92.3631
0.0112	146.3415	6000	5.4837	92.4496
0.0104	170.7317	7000	5.5085	91.7867

Framework versions

Transformers 4.45.2
Pytorch 2.1.0+cu118
Datasets 3.0.1
Tokenizers 0.20.1