---
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-1.0.14-DPO
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# WeniGPT-Agents-Mistral-1.0.0-SFT-1.0.14-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: 0.1709
- Rewards/chosen: 1.9941
- Rewards/rejected: -0.4449
- Rewards/accuracies: 0.8571
- Rewards/margins: 2.4390
- Logps/rejected: -161.0436
- Logps/chosen: -111.4245
- Logits/rejected: -1.8499
- Logits/chosen: -1.8319

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5263        | 0.9677 | 30   | 0.5183          | 0.3988         | -0.0166          | 0.7143             | 0.4154          | -159.6158      | -116.7421    | -1.8403         | -1.8221       |
| 0.2814        | 1.9355 | 60   | 0.3516          | 0.9688         | -0.0208          | 0.7143             | 0.9896          | -159.6299      | -114.8421    | -1.8443         | -1.8259       |
| 0.1778        | 2.9032 | 90   | 0.2655          | 1.3864         | -0.0997          | 0.8571             | 1.4861          | -159.8928      | -113.4503    | -1.8470         | -1.8286       |
| 0.1388        | 3.8710 | 120  | 0.2128          | 1.7020         | -0.2501          | 0.8571             | 1.9521          | -160.3941      | -112.3981    | -1.8494         | -1.8311       |
| 0.1349        | 4.8387 | 150  | 0.1841          | 1.9322         | -0.3766          | 0.8571             | 2.3088          | -160.8158      | -111.6308    | -1.8499         | -1.8319       |
| 0.1178        | 5.8065 | 180  | 0.1709          | 1.9941         | -0.4449          | 0.8571             | 2.4390          | -161.0436      | -111.4245    | -1.8499         | -1.8319       |


### Framework versions

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