---
license: apache-2.0
base_model: Minbyul/mistral-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: mistral-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. -->

# mistral-7b-dpo-full-sft-wo-kqa_silver_wogold

This model is a fine-tuned version of [Minbyul/mistral-7b-wo-kqa_silver_wogold-sft](https://huggingface.co/Minbyul/mistral-7b-wo-kqa_silver_wogold-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0530
- Rewards/chosen: -2.4760
- Rewards/rejected: -21.0723
- Rewards/accuracies: 0.9700
- Rewards/margins: 18.5963
- Logps/rejected: -2709.2131
- Logps/chosen: -407.7003
- Logits/rejected: -2.0225
- Logits/chosen: -2.2276

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2735        | 0.32  | 100  | 0.0529          | -1.3592        | -8.1857          | 0.9700             | 6.8265          | -1420.5509     | -296.0260    | -2.7457         | -2.5375       |
| 0.1321        | 0.63  | 200  | 0.0507          | -2.0405        | -16.8511         | 0.9600             | 14.8106         | -2287.0967     | -364.1557    | -2.2518         | -2.3349       |
| 0.117         | 0.95  | 300  | 0.0531          | -2.4855        | -21.1345         | 0.9700             | 18.6490         | -2715.4331     | -408.6504    | -2.0210         | -2.2273       |


### Framework versions

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