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fine-tuning-Phi2-with-webglm – AI Model by mpachha | AlphaNeural AI
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mpachha
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fine-tuning-Phi2-with-webglm
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peft
safetensors
generated_from_trainer
microsoft/phi-2
adapter
mit
us
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fine-tuning-Phi2-with-webglm
This model is a fine-tuned version of
microsoft/phi-2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5316
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 5
total_train_batch_size: 10
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 100
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.5629
1.0
100
0.5316
Framework versions
PEFT 0.11.1
Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2
