---
base_model: dmis-lab/selfbiorag_7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3
  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-wo-kqa_silver_wogold-ep3

This model is a fine-tuned version of [dmis-lab/selfbiorag_7b](https://huggingface.co/dmis-lab/selfbiorag_7b) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6392
- Rewards/chosen: 0.1232
- Rewards/rejected: -0.0030
- Rewards/accuracies: 0.7527
- Rewards/margins: 0.1262
- Logps/rejected: -171.6258
- Logps/chosen: -150.9050
- Logits/rejected: -1.5645
- Logits/chosen: -1.7964

## 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-07
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6608        | 0.25  | 100  | 0.6631          | 0.1074         | 0.0395           | 0.7107             | 0.0680          | -167.3843      | -152.4830    | -1.5362         | -1.7612       |
| 0.6271        | 0.51  | 200  | 0.6474          | 0.1331         | 0.0272           | 0.7455             | 0.1060          | -168.6118      | -149.9109    | -1.5243         | -1.7495       |
| 0.61          | 0.76  | 300  | 0.6403          | 0.1251         | 0.0020           | 0.7554             | 0.1232          | -171.1355      | -150.7145    | -1.5597         | -1.7911       |


### Framework versions

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