---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-14B-Instruct
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: lambda-qwen2.5-14b-dpo-test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# lambda-qwen2.5-14b-dpo-test

This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4919
- Rewards/chosen: -2.4745
- Rewards/rejected: -3.3729
- Rewards/accuracies: 0.7400
- Rewards/margins: 0.8984
- Logps/rejected: -832.0724
- Logps/chosen: -737.5234
- Logits/rejected: -1.2739
- Logits/chosen: -1.2560

## 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: 8
- total_train_batch_size: 128
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5269        | 0.2094 | 100  | 0.5333          | -1.6756        | -2.3320          | 0.7000             | 0.6564          | -727.9815      | -657.6356    | -1.3952         | -1.3850       |
| 0.5086        | 0.4187 | 200  | 0.5044          | -2.0906        | -2.9287          | 0.7040             | 0.8381          | -787.6511      | -699.1298    | -1.2939         | -1.2773       |
| 0.4787        | 0.6281 | 300  | 0.4948          | -2.2927        | -3.1689          | 0.7320             | 0.8762          | -811.6696      | -719.3386    | -1.2846         | -1.2646       |
| 0.4825        | 0.8375 | 400  | 0.4924          | -2.4470        | -3.3410          | 0.7400             | 0.8939          | -828.8748      | -734.7765    | -1.2644         | -1.2477       |


### Framework versions

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