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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: 0.9913 |
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- Rewards/chosen: -0.0569 |
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- Rewards/rejected: -0.0657 |
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- Rewards/accuracies: 0.5511 |
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- Rewards/margins: 0.0088 |
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- Logps/rejected: -44.0859 |
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- Logps/chosen: -39.7278 |
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- Logits/rejected: -1.5833 |
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- Logits/chosen: -1.5872 |
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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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| 0.9987 | 0.26 | 100 | -2.2313 | -2.2264 | -34.0499 | -37.5528 | 0.9998 | 0.5336 | -0.0002 | 0.0002 | -0.0004 | |
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| 0.9965 | 0.52 | 200 | -2.2252 | -2.2204 | -34.0618 | -37.5790 | 0.9996 | 0.5071 | -0.0003 | 0.0004 | -0.0006 | |
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| 0.9925 | 0.78 | 300 | -2.2214 | -2.2166 | -34.0836 | -37.6063 | 0.9996 | 0.5594 | -0.0005 | 0.0004 | -0.0009 | |
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| 0.986 | 1.04 | 400 | 0.9994 | -0.0014 | -0.0019 | 0.5212 | 0.0006 | -37.7105 | -34.1717 | -2.1877 | -2.1926 | |
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| 0.9781 | 1.3 | 500 | 0.9987 | -0.0031 | -0.0044 | 0.5855 | 0.0013 | -37.9551 | -34.3418 | -2.1137 | -2.1185 | |
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| 0.9774 | 1.56 | 600 | 0.9973 | -0.0073 | -0.0101 | 0.5743 | 0.0027 | -38.5228 | -34.7671 | -2.0162 | -2.0208 | |
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| 0.9688 | 1.82 | 700 | 0.9969 | -0.0143 | -0.0174 | 0.5482 | 0.0031 | -39.2598 | -35.4681 | -1.9235 | -1.9280 | |
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| 0.957 | 2.08 | 800 | 0.9954 | -0.0214 | -0.0260 | 0.5540 | 0.0046 | -40.1194 | -36.1733 | -1.8363 | -1.8407 | |
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| 0.9358 | 2.34 | 900 | 0.9939 | -0.0362 | -0.0423 | 0.5365 | 0.0061 | -41.7483 | -37.6532 | -1.6988 | -1.7029 | |
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| 0.9535 | 2.6 | 1000 | 0.9921 | -0.0511 | -0.0591 | 0.5453 | 0.0079 | -43.4237 | -39.1479 | -1.6143 | -1.6183 | |
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| 0.9616 | 2.86 | 1100 | 0.9916 | -0.0562 | -0.0646 | 0.5453 | 0.0084 | -43.9754 | -39.6505 | -1.5880 | -1.5920 | |
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| 0.9167 | 3.12 | 1200 | 0.9912 | -0.0563 | -0.0651 | 0.5482 | 0.0088 | -44.0289 | -39.6666 | -1.5851 | -1.5890 | |
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| 0.9033 | 3.38 | 1300 | 0.9913 | -0.0570 | -0.0657 | 0.5453 | 0.0087 | -44.0868 | -39.7316 | -1.5817 | -1.5856 | |
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| 0.9285 | 3.64 | 1400 | 0.9912 | -0.0569 | -0.0657 | 0.5395 | 0.0088 | -44.0852 | -39.7216 | -1.5825 | -1.5864 | |
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| 0.9196 | 3.9 | 1500 | 0.9913 | -0.0567 | -0.0655 | 0.5424 | 0.0088 | -44.0648 | -39.7075 | -1.5832 | -1.5871 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
