whisper-small-cv-1 – AI Model by lejonck | AlphaNeural AI

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whisper-small-cv-1

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automatic-speech-recognition

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openai/whisper-small

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whisper-small-cv-1

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

Loss: 0.2809
Wer: 0.2588
Cer: 0.2931

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: 2
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.292	1.0	500	0.2837	0.2614	0.2950
0.1042	2.0	1000	0.2868	0.2584	0.2941
0.04	3.0	1500	0.2966	0.2625	0.2965
0.0102	4.0	2000	0.3444	0.2703	0.2966
0.0106	5.0	2500	0.4016	0.2648	0.2960
0.0018	6.0	3000	0.4035	0.2633	0.2959
0.001	7.0	3500	0.4156	0.2636	0.2956
0.0007	8.0	4000	0.4224	0.2610	0.2955

Framework versions

Transformers 4.55.2
Pytorch 2.7.0+cu126
Datasets 2.19.1
Tokenizers 0.21.4