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--- |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- trl |
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- dpo |
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- generated_from_trainer |
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base_model: norallm/normistral-7b-warm |
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datasets: |
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- hugodk-sch/aftonposten_title_prefs |
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model-index: |
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- name: ap-normistral-7b-align-scan |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ap-normistral-7b-align-scan |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6647 |
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- Rewards/chosen: 0.0868 |
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- Rewards/rejected: 0.0880 |
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- Rewards/accuracies: 0.5108 |
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- Rewards/margins: -0.0012 |
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- Logps/rejected: -35.8687 |
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- Logps/chosen: -32.3467 |
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- Logits/rejected: 99.0734 |
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- Logits/chosen: 99.0806 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 2.0775 | 0.26 | 100 | 1.7337 | -0.0836 | -0.0209 | 0.4747 | -0.0626 | -35.9898 | -32.5360 | 98.9624 | 98.9691 | |
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| 3.1221 | 0.52 | 200 | 1.7165 | -0.0706 | -0.1245 | 0.5278 | 0.0539 | -36.1048 | -32.5217 | 99.1580 | 99.1691 | |
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| 2.4404 | 0.78 | 300 | 1.5174 | 0.1203 | 0.1230 | 0.5108 | -0.0027 | -35.8299 | -32.3095 | 99.0568 | 99.0617 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.1 |
