whisper-noise5 – AI Model by Dearlie | AlphaNeural AI

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Dearlie/
whisper-noise5

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automatic-speech-recognition

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openai/whisper-base

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Whisper Base Noise Ko - Dearlie

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

Loss: 1.0514
Cer: 36.7799

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: 0.0003
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: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
1.6152	0.8780	1000	1.6157	68.7925
1.1303	1.7559	2000	1.2280	52.3127
0.7779	2.6339	3000	1.0609	43.5822
0.4133	3.5119	4000	1.0210	41.4074
0.175	4.3898	5000	1.0462	38.0307
0.0468	5.2678	6000	1.0514	36.7799

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1