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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: 0.5060 |
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- Rewards/chosen: 0.0978 |
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- Rewards/rejected: 0.1310 |
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- Rewards/accuracies: 0.5220 |
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- Rewards/margins: -0.0333 |
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- Logps/rejected: -35.7793 |
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- Logps/chosen: -32.3035 |
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- Logits/rejected: 98.3593 |
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- Logits/chosen: 98.3666 |
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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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| 0.461 | 0.26 | 100 | 0.5000 | 0.0677 | 0.0660 | 0.5158 | 0.0017 | -35.8723 | -32.3464 | 98.6883 | 98.7043 | |
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| 0.3172 | 0.52 | 200 | 0.4956 | 0.0869 | 0.0578 | 0.5133 | 0.0291 | -35.8840 | -32.3190 | 98.4409 | 98.4463 | |
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| 0.3303 | 0.78 | 300 | 0.4980 | 0.1165 | 0.1232 | 0.5017 | -0.0067 | -35.7905 | -32.2767 | 98.3630 | 98.3713 | |
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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 |
