---
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
# base_model: /ML-A100/team/mm/zhangge/models/neo_pt2.6_phase2/sft_ckpts/neo_7B_sft_v0_1_plus/checkpoint-225
# datasets:
# - /ML-A100/team/mm/zhangge/iterativeDPO/data/dataset/Nectar-Starling-RM-34B-rank1-2-origin
model-index:
- name: neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# neo_7B_sft_v0_1_plus-dpo-iter1-beta0_3

This model is a fine-tuned version of [/ML-A100/team/mm/zhangge/models/neo_pt2.6_phase2/sft_ckpts/neo_7B_sft_v0_1_plus/checkpoint-225](https://huggingface.co//ML-A100/team/mm/zhangge/models/neo_pt2.6_phase2/sft_ckpts/neo_7B_sft_v0_1_plus/checkpoint-225) on the /ML-A100/team/mm/zhangge/iterativeDPO/data/dataset/Nectar-Starling-RM-34B-rank1-2-origin dataset.

## 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-06
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- total_train_batch_size: 192
- total_eval_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results



### Framework versions

- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2