base-v2 – AI Model by devkyle | AlphaNeural AI | AlphaNeural AI

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devkyle/
base-v2

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automatic-speech-recognition

generated_from_trainer

openai/whisper-base

endpoints_compatible

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whisper-base-akan

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

Loss: 1.0030
Wer: 41.5869

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: 0.0001
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: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2883	5.0	250	0.7379	70.2488
0.0873	10.0	500	0.8617	49.6246
0.0373	15.0	750	0.9027	47.4165
0.0204	20.0	1000	0.9374	44.5017
0.0078	25.0	1250	0.9861	44.0601
0.0014	30.0	1500	0.9873	42.1758
0.0003	35.0	1750	0.9982	41.4544
0.0003	40.0	2000	1.0030	41.5869

Framework versions

Transformers 4.45.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.1