---
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-live_qa-ep3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# selfbiorag-7b-dpo-full-wo-live_qa-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: 0.6503
- Rewards/chosen: 0.1533
- Rewards/rejected: 0.0496
- Rewards/accuracies: 0.7273
- Rewards/margins: 0.1037
- Logps/rejected: -152.4542
- Logps/chosen: -129.3861
- Logits/rejected: -1.6930
- Logits/chosen: -1.9168

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6586        | 0.22  | 100  | 0.6694          | 0.1304         | 0.0785           | 0.6932             | 0.0520          | -149.5688      | -131.6699    | -1.5849         | -1.7960       |
| 0.6342        | 0.44  | 200  | 0.6581          | 0.1743         | 0.0934           | 0.7273             | 0.0808          | -148.0715      | -127.2864    | -1.5703         | -1.7959       |
| 0.5967        | 0.66  | 300  | 0.6527          | 0.1658         | 0.0685           | 0.7159             | 0.0973          | -150.5620      | -128.1308    | -1.6454         | -1.8741       |
| 0.5979        | 0.88  | 400  | 0.6502          | 0.1544         | 0.0500           | 0.7273             | 0.1043          | -152.4127      | -129.2778    | -1.6898         | -1.9159       |


### Framework versions

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