---
base_model: Minbyul/selfbiorag-7b-wo-kqa_golden-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-kqa_golden
  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-kqa_golden

This model is a fine-tuned version of [Minbyul/selfbiorag-7b-wo-kqa_golden-sft](https://huggingface.co/Minbyul/selfbiorag-7b-wo-kqa_golden-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2401
- Rewards/chosen: -1.0928
- Rewards/rejected: -13.1704
- Rewards/accuracies: 0.8942
- Rewards/margins: 12.0777
- Logps/rejected: -2031.5652
- Logps/chosen: -567.3484
- Logits/rejected: -0.2100
- Logits/chosen: -0.3532

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.249         | 0.31  | 100  | 0.3604          | -0.7724        | -7.8952          | 0.8942             | 7.1228          | -1504.0413     | -535.3107    | -0.2666         | -0.2359       |
| 0.1374        | 0.62  | 200  | 0.2389          | -0.9231        | -8.0656          | 0.9038             | 7.1425          | -1521.0862     | -550.3824    | -0.1753         | -0.2822       |
| 0.0982        | 0.92  | 300  | 0.2413          | -1.0961        | -13.1849         | 0.8942             | 12.0888         | -2033.0142     | -567.6829    | -0.2111         | -0.3569       |


### Framework versions

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