---
license: llama2
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: lmsys/vicuna-7b-v1.5
model-index:
- name: Vicuna-7B-v1.5-ORPO-SALT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Vicuna-7B-v1.5-ORPO-SALT

This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9497
- Rewards/chosen: -0.0879
- Rewards/rejected: -0.0995
- Rewards/accuracies: 0.5164
- Rewards/margins: 0.0116
- Logps/rejected: -0.9948
- Logps/chosen: -0.8787
- Logits/rejected: -0.3581
- Logits/chosen: -0.3775
- Sft Loss: 0.8787
- Odds Ratio Loss: 0.7104

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.0008        | 0.8082 | 500  | 0.9777          | -0.0907        | -0.1019          | 0.5055             | 0.0113          | -1.0193        | -0.9066      | -0.3689         | -0.3878       | 0.9066   | 0.7105          |
| 0.8458        | 1.6165 | 1000 | 0.9560          | -0.0885        | -0.1000          | 0.5191             | 0.0115          | -1.0000        | -0.8850      | -0.3578         | -0.3772       | 0.8850   | 0.7097          |
| 0.9219        | 2.4247 | 1500 | 0.9497          | -0.0879        | -0.0995          | 0.5164             | 0.0116          | -0.9948        | -0.8787      | -0.3581         | -0.3775       | 0.8787   | 0.7104          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1