---
library_name: peft
tags:
- trl
- dpo
- DPO
- WeniGPT
- generated_from_trainer
base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
model-index:
- name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO
  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. -->

# WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO

This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2005
- Rewards/chosen: 1.7621
- Rewards/rejected: -0.7248
- Rewards/accuracies: 1.0
- Rewards/margins: 2.4869
- Logps/rejected: -271.5133
- Logps/chosen: -102.9727
- Logits/rejected: -1.8958
- Logits/chosen: -1.8013

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 180
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5477        | 0.97  | 30   | 0.4843          | 0.4718         | -0.1109          | 0.8571             | 0.5827          | -269.4668      | -107.2735    | -1.8863         | -1.7949       |
| 0.3542        | 1.94  | 60   | 0.3440          | 0.9609         | -0.2516          | 1.0                | 1.2125          | -269.9360      | -105.6431    | -1.8903         | -1.7979       |
| 0.2892        | 2.9   | 90   | 0.2756          | 1.3199         | -0.4182          | 1.0                | 1.7381          | -270.4914      | -104.4467    | -1.8928         | -1.7995       |
| 0.1858        | 3.87  | 120  | 0.2327          | 1.6010         | -0.5696          | 1.0                | 2.1706          | -270.9958      | -103.5094    | -1.8947         | -1.8008       |
| 0.1811        | 4.84  | 150  | 0.2076          | 1.7245         | -0.6925          | 1.0                | 2.4170          | -271.4054      | -103.0979    | -1.8954         | -1.8010       |
| 0.2065        | 5.81  | 180  | 0.2005          | 1.7621         | -0.7248          | 1.0                | 2.4869          | -271.5133      | -102.9727    | -1.8958         | -1.8013       |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2