---
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: 0.4945
- Rewards/chosen: -2.5530
- Rewards/rejected: -3.6159
- Rewards/accuracies: 0.7778
- Rewards/margins: 1.0629
- Logps/rejected: -606.2373
- Logps/chosen: -520.2218
- Logits/rejected: -0.9908
- Logits/chosen: -1.1030

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6212        | 0.1047 | 100  | 0.6321          | -0.3313        | -0.5450          | 0.6944             | 0.2137          | -299.1472      | -298.0506    | -2.0086         | -2.0933       |
| 0.5618        | 0.2094 | 200  | 0.5601          | -0.8198        | -1.3660          | 0.7222             | 0.5461          | -381.2446      | -346.9064    | -1.6694         | -1.7551       |
| 0.54          | 0.3141 | 300  | 0.5265          | -1.5221        | -2.3343          | 0.7460             | 0.8122          | -478.0748      | -417.1275    | -1.0704         | -1.1715       |
| 0.5261        | 0.4187 | 400  | 0.5082          | -1.6553        | -2.5263          | 0.7540             | 0.8710          | -497.2759      | -430.4526    | -1.1014         | -1.2013       |
| 0.5107        | 0.5234 | 500  | 0.5059          | -2.4506        | -3.4250          | 0.75               | 0.9744          | -587.1476      | -509.9848    | -0.9852         | -1.0956       |
| 0.4851        | 0.6281 | 600  | 0.5023          | -2.2726        | -3.2316          | 0.7679             | 0.9590          | -567.8049      | -492.1783    | -0.9970         | -1.1078       |
| 0.4681        | 0.7328 | 700  | 0.4993          | -2.3170        | -3.3688          | 0.7679             | 1.0517          | -581.5197      | -496.6232    | -1.0068         | -1.1190       |
| 0.4852        | 0.8375 | 800  | 0.4950          | -2.3970        | -3.4117          | 0.7738             | 1.0147          | -585.8156      | -504.6183    | -1.0237         | -1.1353       |
| 0.4907        | 0.9422 | 900  | 0.4945          | -2.5678        | -3.6349          | 0.7778             | 1.0671          | -608.1346      | -521.7063    | -0.9901         | -1.1024       |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1