---
library_name: peft
tags:
- trl
- dpo
- DPO
- WeniGPT
- generated_from_trainer
base_model: Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-merged
model-index:
- name: WeniGPT-Agents-Mistral-1.0.0-SFT-1.0.21-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-1.0.0-SFT-1.0.21-DPO

This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-merged) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0520
- Rewards/chosen: 2.3217
- Rewards/rejected: -1.5051
- Rewards/accuracies: 1.0
- Rewards/margins: 3.8268
- Logps/rejected: -167.9981
- Logps/chosen: -107.6077
- Logits/rejected: -1.7717
- Logits/chosen: -1.7573

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3976        | 0.9677 | 30   | 0.3186          | 0.8373         | -0.0381          | 1.0                | 0.8754          | -160.6632      | -115.0300    | -1.7561         | -1.7413       |
| 0.1934        | 1.9355 | 60   | 0.1752          | 1.6472         | -0.5496          | 1.0                | 2.1968          | -163.2207      | -110.9804    | -1.7603         | -1.7456       |
| 0.1058        | 2.9032 | 90   | 0.1096          | 1.9881         | -0.7856          | 1.0                | 2.7737          | -164.4007      | -109.2759    | -1.7637         | -1.7491       |
| 0.0527        | 3.8710 | 120  | 0.0787          | 2.1758         | -1.0246          | 1.0                | 3.2004          | -165.5957      | -108.3371    | -1.7676         | -1.7532       |
| 0.0526        | 4.8387 | 150  | 0.0577          | 2.2762         | -1.3610          | 1.0                | 3.6373          | -167.2778      | -107.8351    | -1.7693         | -1.7549       |
| 0.0529        | 5.8065 | 180  | 0.0520          | 2.3217         | -1.5051          | 1.0                | 3.8268          | -167.9981      | -107.6077    | -1.7717         | -1.7573       |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.19.1