---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-7B-Instruct-1M
tags:
- alignment-handbook
- ndcg
- trl
- generated_from_trainer
- trl
- ndcg
- generated_from_trainer
datasets:
- yangzhao02/ListUltraFeedback
model-index:
- name: qwen2.5-7b-lipo
  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. -->

# qwen2.5-7b-lipo

This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct-1M](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M) on the yangzhao02/ListUltraFeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0017
- Logps: -661.8630
- Logits: -0.6117
- Rank Correct Batch: 16.5203
- Rank Pair Batch: 28.0
- Rank Accuracy Batch: 0.5900

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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

| Training Loss | Epoch  | Step | Validation Loss | Logps     | Logits  | Rank Correct Batch | Rank Pair Batch | Rank Accuracy Batch |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:------------------:|:---------------:|:-------------------:|
| 0.0021        | 0.2672 | 125  | 0.0021          | -582.2852 | -0.6831 | 15.8902            | 28.0            | 0.5675              |
| 0.0019        | 0.5344 | 250  | 0.0018          | -642.7833 | -0.6304 | 16.4431            | 28.0            | 0.5873              |
| 0.0017        | 0.8016 | 375  | 0.0017          | -662.0203 | -0.6116 | 16.5244            | 28.0            | 0.5902              |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.6.0+cu126
- Datasets 2.19.1
- Tokenizers 0.20.3