voice-clone-large-finetune-final – AI Model by neuronbit | AlphaNeural AI

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neuronbit/
voice-clone-large-finetune-final

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automatic-speech-recognition

generated_from_trainer

openai/whisper-large-v3

endpoints_compatible

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voice-clone-large-finetune-final

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4377
Wer: 15.3572

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1607	0.8460	250	0.5163	25.9413
0.0598	1.6920	500	0.4849	24.8444
0.0257	2.5381	750	0.4450	30.4180
0.0141	3.3841	1000	0.4369	19.3003
0.0029	4.2301	1250	0.4267	16.0095
0.0015	5.0761	1500	0.4209	18.4109
0.0063	5.9222	1750	0.4259	19.3300
0.0016	6.7682	2000	0.4341	17.7587
0.0009	7.6142	2250	0.4121	17.0471
0.0013	8.4602	2500	0.4199	16.3653
0.0009	9.3063	2750	0.4233	16.5135
0.001	10.1523	3000	0.4237	16.0688
0.0019	10.9983	3250	0.4230	16.4542
0.0014	11.8443	3500	0.4292	15.8316
0.0007	12.6904	3750	0.4291	15.8316
0.0005	13.5364	4000	0.4321	15.3869
0.0009	14.3824	4250	0.4334	15.2980
0.001	15.2284	4500	0.4344	15.2980
0.0	16.0745	4750	0.4372	15.3572
0.0	16.9205	5000	0.4377	15.3572

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3