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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: CohereForAI/aya-23-8B |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- simonycl/aya-23-8B_advprompter_jailbreak |
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model-index: |
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- name: aya-advprompter |
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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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# aya-advprompter |
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This model is a fine-tuned version of [CohereForAI/aya-23-8B](https://huggingface.co/CohereForAI/aya-23-8B) on the simonycl/aya-23-8B_advprompter_jailbreak dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0459 |
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- Rewards/chosen: 0.0182 |
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- Rewards/rejected: -6.7884 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 6.8065 |
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- Logps/rejected: -867.2261 |
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- Logps/chosen: -114.6688 |
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- Logits/rejected: 0.0796 |
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- Logits/chosen: -0.2307 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 2 |
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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: 0.05 |
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- num_epochs: 2 |
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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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| 0.5229 | 0.3612 | 30 | -0.4619 | -0.3434 | -98.2886 | -212.0101 | 0.5059 | 1.0 | 0.1820 | 0.4182 | -0.2362 | |
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| 0.2411 | 0.7223 | 60 | -0.4067 | -0.2327 | -88.9001 | -330.7860 | 0.2135 | 1.0 | 0.2758 | 1.6998 | -1.4240 | |
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| 0.0634 | 1.0835 | 90 | -0.2580 | -0.0357 | -99.5121 | -607.3592 | 0.0751 | 1.0 | 0.1697 | 4.3594 | -4.1897 | |
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| 0.0452 | 1.4454 | 120 | 0.0532 | 0.0757 | -5.9396 | 1.0 | 6.0153 | -782.3494 | -108.9159 | 0.0380 | -0.2345 | |
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| 0.0307 | 1.8066 | 150 | 0.0459 | 0.0182 | -6.7884 | 1.0 | 6.8065 | -867.2261 | -114.6688 | 0.0796 | -0.2307 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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