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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: 0.7163
- Rewards/chosen: -0.1039
- Rewards/rejected: -0.1729
- Rewards/accuracies: 0.5573
- Rewards/margins: 0.0690
- Logps/rejected: -36.3124
- Logps/chosen: -32.6510
- Logits/rejected: 98.5157
- Logits/chosen: 98.5379
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6859 | 0.26 | 100 | 0.7229 | -0.0559 | -0.0850 | 0.5282 | 0.0290 | -36.1364 | -32.5550 | 98.6727 | 98.6826 |
| 0.5453 | 0.52 | 200 | 0.7068 | -0.1291 | -0.2159 | 0.5332 | 0.0868 | -36.3984 | -32.7014 | 98.4732 | 98.4956 |
| 0.5511 | 0.78 | 300 | 0.7290 | -0.1187 | -0.1591 | 0.5453 | 0.0404 | -36.2848 | -32.6805 | 98.5351 | 98.5572 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 |