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---
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: 0.4955
- Rewards/chosen: 0.0848
- Rewards/rejected: 0.0593
- Rewards/accuracies: 0.5282
- Rewards/margins: 0.0255
- Logps/rejected: -35.8183
- Logps/chosen: -32.2312
- Logits/rejected: 98.3492
- Logits/chosen: 98.3463
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4749 | 0.26 | 100 | 0.5047 | 0.0131 | 0.0430 | 0.4747 | -0.0299 | -35.8591 | -32.4105 | 98.7377 | 98.7500 |
| 0.3843 | 0.52 | 200 | 0.4944 | 0.0238 | -0.0061 | 0.5307 | 0.0299 | -35.9817 | -32.3837 | 98.3784 | 98.3836 |
| 0.363 | 0.78 | 300 | 0.4962 | 0.0856 | 0.0600 | 0.5104 | 0.0256 | -35.8166 | -32.2293 | 98.3704 | 98.3655 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 |