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southmost/
phi2-lora-distilabel-intel-orca-dpo-pairs

Name: phi2-lora-distilabel-intel-orca-dpo-pairs
Availability: InStock

generated_from_trainer

microsoft/phi-2

adapter

mit

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Note from me: This is a fine tuned Phi-2 on Argilla-provided Intel Orca DPO pairs. It's run with the default settings, just with the batch sized at 2 instead of 1. The below was automatically generated by the trainer. It cost about $2.50 to train on RunPod.

phi2-lora-distilabel-intel-orca-dpo-pairs

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: 0.4467
Rewards/chosen: -0.0981
Rewards/rejected: -1.3106
Rewards/accuracies: 0.8410
Rewards/margins: 1.2125
Logps/rejected: -228.4777
Logps/chosen: -209.0628
Logits/rejected: 0.4528
Logits/chosen: 0.2946

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: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.5578	0.78	250	0.4467	-0.0981	-1.3106	0.8410	1.2125	-228.4777	-209.0628	0.4528	0.2946

Framework versions

PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.1.0+cu118
Datasets 2.18.0
Tokenizers 0.15.2

southmost/phi2-lora-distilabel-intel-orca-dpo-pairs

phi2-lora-distilabel-intel-orca-dpo-pairs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

southmost/
phi2-lora-distilabel-intel-orca-dpo-pairs