|
|
--- |
|
|
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 |
