---
base_model: Minbyul/selfbiorag-7b-wo-live_qa-sft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: selfbiorag-7b-dpo-full-sft-wo-live_qa
  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. -->

# selfbiorag-7b-dpo-full-sft-wo-live_qa

This model is a fine-tuned version of [Minbyul/selfbiorag-7b-wo-live_qa-sft](https://huggingface.co/Minbyul/selfbiorag-7b-wo-live_qa-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1422
- Rewards/chosen: -1.2709
- Rewards/rejected: -13.2633
- Rewards/accuracies: 0.9167
- Rewards/margins: 11.9924
- Logps/rejected: -1991.3534
- Logps/chosen: -456.8682
- Logits/rejected: -0.4049
- Logits/chosen: -0.4878

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2635        | 0.3   | 100  | 0.1990          | -0.5114        | -9.8179          | 0.9167             | 9.3065          | -1646.8138     | -380.9204    | -0.1085         | -0.3091       |
| 0.1415        | 0.61  | 200  | 0.1502          | -0.9081        | -11.0651         | 0.9167             | 10.1570         | -1771.5302     | -420.5836    | -0.4280         | -0.4824       |
| 0.0892        | 0.91  | 300  | 0.1421          | -1.2604        | -13.2286         | 0.9167             | 11.9683         | -1987.8828     | -455.8129    | -0.4048         | -0.4887       |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2