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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: 0.9722
- Rewards/chosen: -0.0621
- Rewards/rejected: -0.1987
- Rewards/accuracies: 0.5453
- Rewards/margins: 0.1366
- Logps/rejected: -36.2149
- Logps/chosen: -32.5208
- Logits/rejected: 98.875
- Logits/chosen: 98.9020
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.9567 | 0.26 | 100 | 1.1574 | -0.0132 | 0.0638 | 0.4630 | -0.0769 | -35.8868 | -32.4596 | 98.7233 | 98.7349 |
| 0.8098 | 0.52 | 200 | 1.0545 | -0.0943 | -0.1571 | 0.5278 | 0.0627 | -36.1629 | -32.5611 | 98.8438 | 98.8682 |
| 0.6965 | 0.78 | 300 | 0.9869 | -0.0473 | -0.1807 | 0.5831 | 0.1334 | -36.1923 | -32.5023 | 98.8800 | 98.9053 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 |