---
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-qlora
  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-qlora

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/alignment-handbook/zephyr-7b-sft-qlora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5020
- Rewards/chosen: -2.1712
- Rewards/rejected: -2.9620
- Rewards/accuracies: 0.7054
- Rewards/margins: 0.7908
- Logps/rejected: -535.7245
- Logps/chosen: -475.6829
- Logits/rejected: -1.1754
- Logits/chosen: -1.2812

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- total_eval_batch_size: 24
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6099        | 0.1570 | 100  | 0.5999          | -0.4571        | -0.6755          | 0.6369             | 0.2184          | -307.0734      | -304.2707    | -2.1308         | -2.2191       |
| 0.5468        | 0.3140 | 200  | 0.5354          | -1.2063        | -1.7025          | 0.6815             | 0.4962          | -409.7740      | -379.1950    | -1.5157         | -1.6078       |
| 0.5195        | 0.4710 | 300  | 0.5227          | -1.5981        | -2.2831          | 0.7083             | 0.6849          | -467.8293      | -418.3782    | -1.3523         | -1.4527       |
| 0.4895        | 0.6279 | 400  | 0.5142          | -1.8555        | -2.6654          | 0.6994             | 0.8099          | -506.0622      | -444.1171    | -1.1070         | -1.2180       |
| 0.4992        | 0.7849 | 500  | 0.5019          | -2.3330        | -3.1029          | 0.7054             | 0.7699          | -549.8137      | -491.8629    | -1.1520         | -1.2589       |
| 0.5001        | 0.9419 | 600  | 0.5021          | -2.1712        | -2.9608          | 0.7083             | 0.7896          | -535.6057      | -475.6837    | -1.1768         | -1.2825       |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.1.2
- Datasets 3.0.1
- Tokenizers 0.20.1