---
license: apache-2.0
base_model: BioMistral/BioMistral-7B
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: biomistral-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. -->

# biomistral-7b-dpo-full-wo-kqa_silver_wogold-ep3

This model is a fine-tuned version of [BioMistral/BioMistral-7B](https://huggingface.co/BioMistral/BioMistral-7B) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5095
- Rewards/chosen: -0.5198
- Rewards/rejected: -1.3097
- Rewards/accuracies: 0.7480
- Rewards/margins: 0.7899
- Logps/rejected: -355.7885
- Logps/chosen: -252.1618
- Logits/rejected: 0.4827
- Logits/chosen: -1.3398

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.34          | 0.4   | 100  | 0.5716          | -0.2893        | -0.6625          | 0.7202             | 0.3731          | -291.0631      | -229.1131    | 0.0163          | -1.5214       |
| 0.2189        | 0.79  | 200  | 0.5083          | -0.4815        | -1.2309          | 0.75               | 0.7494          | -347.9087      | -248.3297    | 0.4307          | -1.3596       |


### Framework versions

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