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whisper-base-gcf-lora-r4 – AI Model by GwadaDLT | AlphaNeural AI
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whisper-base-gcf-lora-r4
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peft
tensorboard
safetensors
adapter
lora
transformers
openai/whisper-base
apache-2.0
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whisper-base-gcf-lora-r4
This model is a fine-tuned version of
openai/whisper-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 4.0766
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: 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: 50
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
2.0893
1.4085
200
4.5989
1.7421
2.8169
400
4.2826
1.6664
4.2254
600
4.1532
1.6286
5.6338
800
4.0920
1.5483
7.0423
1000
4.0766
Framework versions
PEFT 0.18.1
Transformers 5.5.0
Pytorch 2.4.1+cu124
Datasets 3.6.0
Tokenizers 0.22.2
