---
license: apache-2.0
base_model: Minbyul/mistral-7b-wo-kqa_golden-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_golden
  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_golden

This model is a fine-tuned version of [Minbyul/mistral-7b-wo-kqa_golden-sft](https://huggingface.co/Minbyul/mistral-7b-wo-kqa_golden-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0018
- Rewards/chosen: -0.4458
- Rewards/rejected: -10.1099
- Rewards/accuracies: 1.0
- Rewards/margins: 9.6641
- Logps/rejected: -1564.3792
- Logps/chosen: -241.2112
- Logits/rejected: -2.0516
- Logits/chosen: -1.3414

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2478        | 0.31  | 100  | 0.0352          | -0.1739        | -4.4264          | 1.0                | 4.2525          | -996.0294      | -214.0196    | -2.9200         | -2.1162       |
| 0.1385        | 0.61  | 200  | 0.0041          | -0.3360        | -8.1997          | 1.0                | 7.8637          | -1373.3590     | -230.2282    | -2.3336         | -1.6287       |
| 0.0899        | 0.92  | 300  | 0.0019          | -0.4479        | -10.0624         | 1.0                | 9.6145          | -1559.6263     | -241.4165    | -2.0553         | -1.3416       |


### Framework versions

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