---
base_model: /apdcephfs_cq10_1567347/share_1567347/share_info/llm_models/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- /apdcephfs_cq10_1567347/share_1567347/mingxiaoli/tmp_data/ultrafeedback_binarized
model-index:
- name: zephyr-7b-Database-SimPO+_bs2ga8
  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. -->

# zephyr-7b-Database-SimPO+_bs2ga8

This model is a fine-tuned version of [/apdcephfs_cq10_1567347/share_1567347/share_info/llm_models/zephyr-7b-sft-full](https://huggingface.co//apdcephfs_cq10_1567347/share_1567347/share_info/llm_models/zephyr-7b-sft-full) on the /apdcephfs_cq10_1567347/share_1567347/mingxiaoli/tmp_data/ultrafeedback_binarized 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-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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

- Transformers 4.41.0
- Pytorch 2.3.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1