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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-32B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: lambda-qwen2.5-32b-dpo-test
  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. -->

# lambda-qwen2.5-32b-dpo-test

This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co./Qwen/Qwen2.5-32B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Rewards/chosen: -10.0873
- Rewards/rejected: -25.9319
- Rewards/accuracies: 1.0
- Rewards/margins: 15.8446
- Logps/rejected: -3031.2175
- Logps/chosen: -1365.4342
- Logits/rejected: -0.2882
- Logits/chosen: -0.0014

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0103        | 0.2618 | 100  | 0.0060          | -8.5159        | -18.7731         | 1.0                | 10.2572         | -2315.3333     | -1208.2968   | -0.5485         | -0.2481       |
| 0.0005        | 0.5236 | 200  | 0.0005          | -9.9255        | -24.9117         | 1.0                | 14.9862         | -2929.1948     | -1349.2588   | -0.3723         | -0.0661       |
| 0.0005        | 0.7853 | 300  | 0.0004          | -10.0873       | -25.9319         | 1.0                | 15.8446         | -3031.2175     | -1365.4342   | -0.2882         | -0.0014       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1