---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: alignment-handbook/zephyr-7b-sft-full
datasets:
- generation/UF6k
model-index:
- name: zephyr-dpop-qlora-uf-oursuf6k-5e-6
  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-dpop-qlora-uf-oursuf6k-5e-6

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 generation/UF6k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0972
- Positive Losses: 4.6136
- Dpo Losses: 0.6513
- Rewards/chosen: 0.1036
- Rewards/rejected: -0.0071
- Rewards/accuracies: 0.6270
- Rewards/margins: 0.1107
- Rewards/margins Max: 0.4366
- Rewards/margins Min: -0.1898
- Rewards/margins Std: 0.2797
- Logps/rejected: -259.8883
- Logps/chosen: -274.8616
- Logits/rejected: -2.7883
- Logits/chosen: -2.8318

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- 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 | Positive Losses | Dpo Losses | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Rewards/margins Max | Rewards/margins Min | Rewards/margins Std | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:----------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6612        | 0.15  | 100  | 0.7167          | 0.3423          | 0.6805     | 0.0814         | 0.0535           | 0.5913             | 0.0279          | 0.1341              | -0.0698             | 0.0908              | -253.8317      | -277.0839    | -2.8097         | -2.8549       |
| 0.6652        | 0.29  | 200  | 0.7424          | 0.6158          | 0.6684     | 0.1444         | 0.0868           | 0.6071             | 0.0576          | 0.2387              | -0.1086             | 0.1564              | -250.5054      | -270.7805    | -2.7612         | -2.8047       |
| 0.6493        | 0.44  | 300  | 0.7586          | 0.7357          | 0.6609     | 0.1701         | 0.0950           | 0.6151             | 0.0751          | 0.2766              | -0.1065             | 0.1714              | -249.6817      | -268.2108    | -2.7656         | -2.8106       |
| 0.6224        | 0.58  | 400  | 0.9943          | 3.3747          | 0.6529     | 0.1119         | 0.0109           | 0.6389             | 0.1009          | 0.3836              | -0.1621             | 0.2434              | -258.0921      | -274.0359    | -2.7767         | -2.8199       |
| 0.5674        | 0.73  | 500  | 1.1831          | 5.7365          | 0.6565     | 0.0641         | -0.0334          | 0.6270             | 0.0975          | 0.4143              | -0.1884             | 0.2702              | -262.5242      | -278.8098    | -2.7934         | -2.8376       |
| 0.5749        | 0.88  | 600  | 1.0992          | 4.5979          | 0.6512     | 0.1035         | -0.0073          | 0.6190             | 0.1109          | 0.4368              | -0.1884             | 0.2790              | -259.9164      | -274.8698    | -2.7839         | -2.8279       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2