---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
  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-dpo-full

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5020
- Rewards/chosen: -0.8985
- Rewards/rejected: -1.8744
- Rewards/accuracies: 0.7812
- Rewards/margins: 0.9759
- Logps/rejected: -450.1291
- Logps/chosen: -352.4258
- Logits/rejected: 1.7371
- Logits/chosen: 0.9003

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5709        | 0.2092 | 100  | 0.5765          | -0.3415        | -0.8321          | 0.7305             | 0.4906          | -345.8958      | -296.7220    | -1.0885         | -1.2465       |
| 0.5427        | 0.4184 | 200  | 0.5256          | -0.7352        | -1.5375          | 0.7695             | 0.8022          | -416.4311      | -336.0986    | 0.9059          | 0.1815        |
| 0.4892        | 0.6276 | 300  | 0.5082          | -0.8910        | -1.8210          | 0.7695             | 0.9300          | -444.7822      | -351.6719    | 1.3892          | 0.5828        |
| 0.5037        | 0.8368 | 400  | 0.5031          | -0.8365        | -1.7881          | 0.7852             | 0.9517          | -441.4968      | -346.2211    | 1.6106          | 0.7959        |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.19.1