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---
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: NorLLM-AI/NorMistral-7B
datasets:
- hugodk-sch/aftonposten_title_prefs
model-index:
- name: norllm-ai-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. -->
# norllm-ai-normistral-7b-align-scan
This model is a fine-tuned version of [data/norllm-ai-normistral-7b-sft-qlora](https://huggingface.co/data/norllm-ai-normistral-7b-sft-qlora) on the hugodk-sch/aftonposten_title_prefs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9105
- Rewards/chosen: -0.0836
- Rewards/rejected: -0.1783
- Rewards/accuracies: 0.5515
- Rewards/margins: 0.0947
- Logps/rejected: -35.1438
- Logps/chosen: -31.4914
- Logits/rejected: -2.8211
- Logits/chosen: -2.8232
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.8436 | 0.26 | 100 | 0.9278 | -0.0021 | -0.0777 | 0.5984 | 0.0756 | -34.8925 | -31.2877 | -2.8097 | -2.8124 |
| 0.7459 | 0.52 | 200 | 0.9159 | -0.0693 | -0.1587 | 0.5835 | 0.0894 | -35.0949 | -31.4556 | -2.8227 | -2.8250 |
| 0.665 | 0.78 | 300 | 0.9202 | -0.0777 | -0.1629 | 0.5656 | 0.0852 | -35.1054 | -31.4766 | -2.8221 | -2.8242 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 |