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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: 0.6864 |
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- Rewards/chosen: -0.0790 |
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- Rewards/rejected: -0.1771 |
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- Rewards/accuracies: 0.5685 |
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- Rewards/margins: 0.0982 |
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- Logps/rejected: -36.4094 |
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- Logps/chosen: -32.6406 |
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- Logits/rejected: 98.4364 |
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- Logits/chosen: 98.4629 |
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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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| 0.6649 | 0.26 | 100 | 0.7134 | -0.0147 | -0.0314 | 0.5220 | 0.0167 | -36.0449 | -32.4799 | 98.6822 | 98.6961 | |
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| 0.6015 | 0.52 | 200 | 0.6984 | -0.1481 | -0.2178 | 0.5403 | 0.0696 | -36.5109 | -32.8134 | 98.4369 | 98.4609 | |
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| 0.5603 | 0.78 | 300 | 0.7084 | -0.0908 | -0.1390 | 0.5399 | 0.0482 | -36.3141 | -32.6701 | 98.4570 | 98.4833 | |
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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 |
