ZhangShenao_-_SELM-Phi-3-mini-4k-instruct-iter-3-4bits – AI Model by RichardErkhov | AlphaNeural AI

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ZhangShenao_-_SELM-Phi-3-mini-4k-instruct-iter-3-4bits

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SELM-Phi-3-mini-4k-instruct-iter-3 - bnb 4bits

Model creator: https://huggingface.co/ZhangShenao/
Original model: https://huggingface.co/ZhangShenao/SELM-Phi-3-mini-4k-instruct-iter-3/

Original model description:

license: mit base_model: ZhangShenao/SELM-Phi-3-mini-4k-instruct-iter-2 tags:

alignment-handbook
dpo
trl
selm datasets:
HuggingFaceH4/ultrafeedback_binarized model-index:
name: SELM-Phi-3-mini-4k-instruct-iter-3 results: []

Self-Exploring Language Models: Active Preference Elicitation for Online Alignment.

SELM-Phi-3-mini-4k-instruct-iter-3

This model is a fine-tuned version of ZhangShenao/SELM-Phi-3-mini-4k-instruct-iter-2 using synthetic data based on on the HuggingFaceH4/ultrafeedback_binarized dataset.

Model description

Model type: A 3.8B parameter Phi3-instruct-based Self-Exploring Language Models (SELM).
License: MIT

Results

	AlpacaEval 2.0 (LC WR)	MT-Bench (Average)
SELM-Phi-3-mini-4k-instruct-iter-3	27.98	8.32
SELM-Phi-3-mini-4k-instruct-iter-2	26.79	8.44
SELM-Phi-3-mini-4k-instruct-iter-1	27.33	8.37
Phi-3-mini-4k-instruct	23.05	8.12

Our model also ranks highly on WildBench! 🔥

Training hyperparameters

The following hyperparameters were used during training:

alpha: 0.001
beta: 0.01
train_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
num_epochs: 1

Framework versions

Transformers 4.40.2
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.19.1