---
base_model: Minbyul/selfbiorag-7b-wo-kqa_silver_wogold-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_silver_wogold
  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_silver_wogold

This model is a fine-tuned version of [Minbyul/selfbiorag-7b-wo-kqa_silver_wogold-sft](https://huggingface.co/Minbyul/selfbiorag-7b-wo-kqa_silver_wogold-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3027
- Rewards/chosen: -1.2987
- Rewards/rejected: -5.2535
- Rewards/accuracies: 0.8697
- Rewards/margins: 3.9549
- Logps/rejected: -1323.0533
- Logps/chosen: -663.1464
- Logits/rejected: -0.3508
- Logits/chosen: -0.2498

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2357        | 0.35  | 100  | 0.3364          | -0.8114        | -3.4524          | 0.8579             | 2.6410          | -1142.9419     | -614.4251    | -0.0367         | 0.0065        |
| 0.154         | 0.71  | 200  | 0.3009          | -0.9868        | -4.1905          | 0.8632             | 3.2037          | -1216.7521     | -631.9589    | -0.3156         | -0.2396       |


### Framework versions

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