README.md

metadata

library_name: peft
license: mit
base_model: microsoft/Phi-3-mini-128k-instruct
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Adapter-Phi-3-mini-128k-instruct-lora-hrdx-gptq
    results: []

Adapter-Phi-3-mini-128k-instruct-lora-hrdx-gptq

This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.1900

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: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• 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
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.3444	30	2.3647
No log	2.6889	60	2.1900

Framework versions

• PEFT 0.13.2
• Transformers 4.46.2
• Pytorch 2.4.0+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3