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realDataFineTune – AI Model by MichaelBr | AlphaNeural AI
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MichaelBr
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realDataFineTune
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peft
tensorboard
safetensors
trl
sft
generated_from_trainer
microsoft/Phi-3-mini-4k-instruct
adapter
mit
us
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realDataFineTune
This model is a fine-tuned version of
microsoft/Phi-3-mini-4k-instruct
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 12.1175
eval_runtime: 379.7612
eval_samples_per_second: 15.407
eval_steps_per_second: 3.852
step: 0
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: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.03
lr_scheduler_warmup_steps: 20
training_steps: 1000
Framework versions
Transformers 4.40.1
Pytorch 2.1.0+cpu
Datasets 2.19.0
Tokenizers 0.19.1
Training procedure
Framework versions
PEFT 0.6.2
