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phi-3-law-br – AI Model by jersobh | AlphaNeural AI
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jersobh
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phi-3-law-br
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peft
safetensors
generated_from_trainer
microsoft/Phi-3-mini-4k-instruct
adapter
mit
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phi-3-law-br
This model is a fine-tuned version of
microsoft/Phi-3-mini-4k-instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.9687
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
1
1.9751
No log
2.0
2
1.9708
No log
3.0
3
1.9687
Framework versions
PEFT 0.14.0
Transformers 4.48.0
Pytorch 2.7.0.dev20250220+cpu
Datasets 3.2.0
Tokenizers 0.21.0
