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kahilwa-fit – AI Model by pepe213 | AlphaNeural AI
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pepe213
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kahilwa-fit
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peft
tensorboard
safetensors
generated_from_trainer
microsoft/Phi-4-mini-instruct
adapter
mit
us
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kahilwa-fit
This model is a fine-tuned version of
microsoft/Phi-4-mini-instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5706
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: 0.0002
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT 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: 2
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.8879
0.9714
17
0.5706
Framework versions
PEFT 0.14.0
Transformers 4.50.3
Pytorch 2.6.0+cu124
Tokenizers 0.21.1
