---
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-1.0.6-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-1.0.6-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: 0.4369
- Rewards/chosen: 1.0224
- Rewards/rejected: -0.1812
- Rewards/accuracies: 0.5
- Rewards/margins: 1.2036
- Logps/rejected: -55.7310
- Logps/chosen: -34.8112
- Logits/rejected: -1.8517
- Logits/chosen: -1.8185

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 90
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5772        | 1.94  | 30   | 0.5171          | 0.5191         | -0.0654          | 0.5                | 0.5845          | -55.3450       | -36.4889     | -1.8456         | -1.8132       |
| 0.5125        | 3.87  | 60   | 0.4517          | 0.8981         | -0.1507          | 0.5                | 1.0487          | -55.6293       | -35.2258     | -1.8501         | -1.8170       |
| 0.491         | 5.81  | 90   | 0.4369          | 1.0224         | -0.1812          | 0.5                | 1.2036          | -55.7310       | -34.8112     | -1.8517         | -1.8185       |


### Framework versions

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