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--- |
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library_name: peft |
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tags: |
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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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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 [NbAiLab/nb-gpt-j-6B-v2](https://huggingface.co./NbAiLab/nb-gpt-j-6B-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4998 |
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- Rewards/chosen: 0.0042 |
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- Rewards/rejected: 0.0036 |
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- Rewards/accuracies: 0.5137 |
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- Rewards/margins: 0.0006 |
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- Logps/rejected: -37.5046 |
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- Logps/chosen: -34.0207 |
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- Logits/rejected: -2.2382 |
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- Logits/chosen: -2.2431 |
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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-07 |
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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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| 0.4987 | 0.26 | 100 | 0.4994 | 0.0049 | 0.0020 | 0.5075 | 0.0029 | -37.5100 | -34.0182 | -2.2389 | -2.2437 | |
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| 0.4979 | 0.52 | 200 | 0.4998 | 0.0039 | 0.0031 | 0.4863 | 0.0008 | -37.5062 | -34.0214 | -2.2384 | -2.2432 | |
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| 0.4978 | 0.78 | 300 | 0.4998 | 0.0042 | 0.0036 | 0.5137 | 0.0006 | -37.5046 | -34.0207 | -2.2382 | -2.2431 | |
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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 |
