---
license: mit
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: TomGrc/FusionNet_7Bx2_MoE_v0.1
model-index:
- name: stealth-finance-v2-dpo-adapter
  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. -->

# stealth-finance-v2-dpo-adapter

This model is a fine-tuned version of [TomGrc/FusionNet_7Bx2_MoE_v0.1](https://huggingface.co/TomGrc/FusionNet_7Bx2_MoE_v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1290
- Rewards/chosen: -0.1799
- Rewards/rejected: -6.0696
- Rewards/accuracies: 0.8597
- Rewards/margins: 5.8897
- Logps/rejected: -324.0384
- Logps/chosen: -275.3572
- Logits/rejected: -0.7749
- Logits/chosen: -0.7773

## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3593        | 1.0   | 3280 | 0.1290          | -0.1799        | -6.0696          | 0.8597             | 5.8897          | -324.0384      | -275.3572    | -0.7749         | -0.7773       |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0