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KasuleTrevor/
cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial

Name: cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial
Availability: InStock

transformers

safetensors

whisper

automatic-speech-recognition

generated_from_trainer

sulaimank/whisper-small-luganda-400hrs

finetune

apache-2.0

endpoints_compatible

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cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial

This model is a fine-tuned version of sulaimank/whisper-small-luganda-400hrs on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2707
Wer: 0.6701
Cer: 0.3993

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: polynomial
lr_scheduler_warmup_steps: 300
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.3639	0.6784	500	1.5276	0.7000	0.4139
1.0537	1.3569	1000	1.3568	0.6768	0.4016
0.9755	2.0353	1500	1.3054	0.6754	0.4010
1.1049	2.7137	2000	1.2845	0.6732	0.3984
0.9403	3.3921	2500	1.2777	0.6747	0.3990
1.0213	4.0706	3000	1.2733	0.6728	0.3976
1.0177	4.7490	3500	1.2721	0.6696	0.3972
0.9417	5.4274	4000	1.2703	0.6683	0.3959
0.9993	6.1058	4500	1.2707	0.6717	0.3996
0.9101	6.7843	5000	1.2707	0.6701	0.3993

Framework versions

Transformers 4.57.6
Pytorch 2.7.1+cu118
Datasets 3.6.0
Tokenizers 0.22.2

KasuleTrevor/cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial

cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

KasuleTrevor/
cdli-whisper-lg-sulaimank-decoder-a40-5e-5-polynomial