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cdli-whisper-en-ug-ke-openai-large-v3-full-a40-1500-fresh – AI Model by KasuleTrevor | AlphaNeural AI
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cdli-whisper-en-ug-ke-openai-large-v3-full-a40-1500-fresh
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
cdli/ugandan_english_nonstandard_speech_v1.0
openai/whisper-large-v3
finetune
apache-2.0
endpoints_compatible
us
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cdli-whisper-en-ug-ke-openai-large-v3-full-a40-1500-fresh
This model is a fine-tuned version of
openai/whisper-large-v3
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6603
Wer: 0.2533
Cer: 0.1741
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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: constant_with_warmup
lr_scheduler_warmup_steps: 150
training_steps: 1500
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.5387
1.6967
500
0.6719
0.2632
0.1803
0.5173
3.3908
1000
0.6613
0.2599
0.1791
0.412
5.0850
1500
0.6603
0.2533
0.1741
Framework versions
Transformers 4.57.6
Pytorch 2.7.1+cu118
Datasets 3.6.0
Tokenizers 0.22.2
