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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: NbAiLab/nb-gpt-j-6B-v2 |
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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: aftonposten-6b-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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# aftonposten-6b-align-scan |
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This model is a fine-tuned version of [data/ap-gpt-j-6b-sft-qlora-04-08](https://huggingface.co./data/ap-gpt-j-6b-sft-qlora-04-08) 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: 0.9173 |
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- Rewards/chosen: -0.0874 |
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- Rewards/rejected: -0.1849 |
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- Rewards/accuracies: 0.5743 |
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- Rewards/margins: 0.0975 |
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- Logps/rejected: -37.7220 |
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- Logps/chosen: -34.1316 |
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- Logits/rejected: -2.2003 |
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- Logits/chosen: -2.2051 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |
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|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| |
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| 0.8913 | 0.26 | 100 | -2.2322 | -2.2273 | -34.0407 | -37.5405 | 0.9845 | 0.5195 | -0.0055 | 0.0159 | -0.0215 | |
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| 0.7293 | 0.52 | 200 | -2.2286 | -2.2238 | -34.0537 | -37.5811 | 0.9602 | 0.5714 | -0.0172 | 0.0408 | -0.0580 | |
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| 0.6144 | 0.78 | 300 | -2.2249 | -2.2201 | -34.0866 | -37.6032 | 0.9713 | 0.5282 | -0.0468 | 0.0310 | -0.0779 | |
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| 0.3632 | 1.04 | 400 | 0.9495 | -0.0909 | -0.1434 | 0.5602 | 0.0525 | -37.6760 | -34.1355 | -2.2076 | -2.2125 | |
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| 0.2994 | 1.3 | 500 | 0.9461 | -0.1647 | -0.2318 | 0.5540 | 0.0671 | -37.7742 | -34.2176 | -2.2162 | -2.2210 | |
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| 0.3408 | 1.56 | 600 | 0.9077 | -0.0675 | -0.1694 | 0.5868 | 0.1019 | -37.7048 | -34.1096 | -2.2017 | -2.2066 | |
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| 0.2796 | 1.82 | 700 | 0.9425 | -0.0929 | -0.1626 | 0.5569 | 0.0697 | -37.6973 | -34.1378 | -2.2012 | -2.2061 | |
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| 0.1052 | 2.08 | 800 | 0.9125 | -0.0848 | -0.1863 | 0.5926 | 0.1015 | -37.7236 | -34.1288 | -2.2003 | -2.2051 | |
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| 0.095 | 2.34 | 900 | 0.9005 | -0.0802 | -0.1942 | 0.5540 | 0.1140 | -37.7324 | -34.1237 | -2.2019 | -2.2067 | |
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| 0.123 | 2.6 | 1000 | 0.9194 | -0.0907 | -0.1876 | 0.5511 | 0.0969 | -37.7251 | -34.1353 | -2.1994 | -2.2043 | |
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| 0.0894 | 2.86 | 1100 | 0.9182 | -0.0915 | -0.1890 | 0.5336 | 0.0976 | -37.7267 | -34.1362 | -2.2001 | -2.2050 | |
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| 0.1086 | 3.12 | 1200 | 0.9023 | -0.0864 | -0.1976 | 0.5627 | 0.1112 | -37.7362 | -34.1306 | -2.2006 | -2.2054 | |
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| 0.0577 | 3.38 | 1300 | 0.9154 | -0.0922 | -0.1935 | 0.5598 | 0.1013 | -37.7317 | -34.1370 | -2.2002 | -2.2050 | |
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| 0.0375 | 3.64 | 1400 | 0.9233 | -0.0896 | -0.1810 | 0.5569 | 0.0914 | -37.7178 | -34.1342 | -2.2002 | -2.2050 | |
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| 0.0724 | 3.9 | 1500 | 0.9176 | -0.0906 | -0.1873 | 0.5627 | 0.0967 | -37.7248 | -34.1353 | -2.2000 | -2.2049 | |
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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 |
