---
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: norallm/normistral-7b-warm
datasets:
- hugodk-sch/aftonposten_title_prefs
model-index:
- name: ap-normistral-7b-align-scan
  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. -->

# ap-normistral-7b-align-scan

This model is a fine-tuned version of [data/ap-normistral-7b-sft-qlora](https://huggingface.co/data/ap-normistral-7b-sft-qlora) on the hugodk-sch/aftonposten_title_prefs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4992
- Rewards/chosen: 0.0239
- Rewards/rejected: 0.0174
- Rewards/accuracies: 0.4892
- Rewards/margins: 0.0064
- Logps/rejected: -35.7921
- Logps/chosen: -32.2044
- Logits/rejected: 98.2668
- Logits/chosen: 98.2727

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4933        | 0.26  | 100  | 0.5023          | 0.0062         | 0.0168           | 0.4498             | -0.0106         | -35.7990       | -32.3816     | 98.6627         | 98.6788       |
| 0.4602        | 0.52  | 200  | 0.4967          | 0.0067         | -0.0120          | 0.5511             | 0.0188          | -36.0870       | -32.3759     | 98.3410         | 98.3552       |
| 0.4586        | 0.78  | 300  | 0.4994          | 0.0186         | 0.0126           | 0.5129             | 0.0060          | -35.8407       | -32.2572     | 98.2712         | 98.2791       |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1