---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: SausageLM-7b-Instruct-v0.01-dpo-qlora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SausageLM-7b-Instruct-v0.01-dpo-qlora

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4204
- Rewards/chosen: -1.9644
- Rewards/rejected: -3.5978
- Rewards/accuracies: 0.8020
- Rewards/margins: 1.6333
- Logps/rejected: -778.7791
- Logps/chosen: -552.1046
- Logits/rejected: 1.3639
- Logits/chosen: 0.3998

## 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-06
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4906        | 0.08  | 300  | 0.5340          | -1.1814        | -1.8425          | 0.7310             | 0.6611          | -603.2533      | -473.8014    | -1.6234         | -1.7536       |
| 0.4794        | 0.16  | 600  | 0.4701          | -1.3882        | -2.4799          | 0.7700             | 1.0918          | -666.9945      | -494.4773    | 1.2460          | 0.4450        |
| 0.4519        | 0.24  | 900  | 0.4566          | -1.4239        | -2.6724          | 0.7730             | 1.2485          | -686.2431      | -498.0537    | 1.0803          | 0.1979        |
| 0.4034        | 0.31  | 1200 | 0.4487          | -1.9028        | -3.5170          | 0.7870             | 1.6142          | -770.7061      | -545.9451    | 1.7156          | 0.7244        |
| 0.4193        | 0.39  | 1500 | 0.4420          | -1.8864        | -3.4847          | 0.7840             | 1.5983          | -767.4712      | -544.3021    | 0.9998          | 0.0019        |
| 0.409         | 0.47  | 1800 | 0.4365          | -2.0591        | -3.7221          | 0.7920             | 1.6630          | -791.2130      | -561.5723    | 1.4876          | 0.5341        |
| 0.4037        | 0.55  | 2100 | 0.4334          | -2.1275        | -3.8835          | 0.7970             | 1.7560          | -807.3529      | -568.4110    | 1.9485          | 0.9489        |
| 0.3829        | 0.63  | 2400 | 0.4248          | -1.8791        | -3.4902          | 0.8010             | 1.6111          | -768.0193      | -543.5670    | 1.5421          | 0.5047        |
| 0.47          | 0.71  | 2700 | 0.4211          | -1.8565        | -3.4027          | 0.8030             | 1.5462          | -759.2699      | -541.3088    | 1.5152          | 0.5343        |
| 0.3769        | 0.79  | 3000 | 0.4205          | -1.9199        | -3.5317          | 0.8010             | 1.6119          | -772.1762      | -547.6463    | 1.5142          | 0.5326        |
| 0.3921        | 0.86  | 3300 | 0.4216          | -2.0430        | -3.7240          | 0.8050             | 1.6810          | -791.3992      | -559.9616    | 1.5287          | 0.5531        |
| 0.4249        | 0.94  | 3600 | 0.4204          | -1.9591        | -3.5883          | 0.8000             | 1.6292          | -777.8283      | -551.5704    | 1.3533          | 0.3917        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0