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---
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
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. -->
# Vicuna-7B-v1.5-ORPO
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0073
- Rewards/chosen: -0.0940
- Rewards/rejected: -0.1081
- Rewards/accuracies: 0.5160
- Rewards/margins: 0.0141
- Logps/rejected: -1.0807
- Logps/chosen: -0.9399
- Logits/rejected: -0.2988
- Logits/chosen: -0.3321
- Sft Loss: 0.9399
- Odds Ratio Loss: 0.6739
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.0913 | 0.8891 | 500 | 1.0354 | -0.0968 | -0.1107 | 0.5180 | 0.0140 | -1.1075 | -0.9676 | -0.3176 | -0.3490 | 0.9676 | 0.6776 |
| 1.0328 | 1.7782 | 1000 | 1.0126 | -0.0945 | -0.1086 | 0.5160 | 0.0141 | -1.0856 | -0.9451 | -0.2979 | -0.3308 | 0.9451 | 0.6748 |
| 0.9998 | 2.6673 | 1500 | 1.0073 | -0.0940 | -0.1081 | 0.5160 | 0.0141 | -1.0807 | -0.9399 | -0.2988 | -0.3321 | 0.9399 | 0.6739 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |