---
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: 0.4850
- Rewards/chosen: 0.1654
- Rewards/rejected: 0.0857
- Rewards/accuracies: 0.5399
- Rewards/margins: 0.0797
- Logps/rejected: -35.8594
- Logps/chosen: -32.2364
- Logits/rejected: 98.4059
- Logits/chosen: 98.4070

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4705        | 0.26  | 100  | 0.4947          | 0.1342         | 0.1226           | 0.4896             | 0.0116          | -35.8133       | -32.2754     | 98.6750         | 98.6871       |
| 0.3097        | 0.52  | 200  | 0.4910          | 0.1604         | 0.1008           | 0.5482             | 0.0596          | -35.8405       | -32.2427     | 98.4702         | 98.4771       |
| 0.3066        | 0.78  | 300  | 0.4855          | 0.1659         | 0.0986           | 0.5282             | 0.0673          | -35.8433       | -32.2358     | 98.4267         | 98.4293       |


### Framework versions

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