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--- |
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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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model-index: |
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- name: arceeai-cpt-sft-dpo-full |
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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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# arceeai-cpt-sft-dpo-full |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4290 |
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- Rewards/chosen: -2.1400 |
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- Rewards/rejected: -3.3730 |
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- Rewards/accuracies: 0.7680 |
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- Rewards/margins: 1.2330 |
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- Logps/rejected: -667.6970 |
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- Logps/chosen: -599.8088 |
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- Logits/rejected: -3.8772 |
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- Logits/chosen: -3.7995 |
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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: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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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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| 0.6051 | 0.1 | 100 | 0.5848 | -0.2214 | -0.5948 | 0.6920 | 0.3733 | -389.8707 | -407.9477 | -3.9800 | -3.8777 | |
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| 0.5134 | 0.21 | 200 | 0.5025 | -1.5935 | -2.5024 | 0.7160 | 0.9089 | -580.6380 | -545.1561 | -3.9154 | -3.8176 | |
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| 0.4489 | 0.31 | 300 | 0.4614 | -1.5620 | -2.6097 | 0.7760 | 1.0477 | -591.3610 | -542.0072 | -3.7594 | -3.6703 | |
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| 0.4359 | 0.42 | 400 | 0.4467 | -2.0879 | -3.2160 | 0.7680 | 1.1281 | -651.9947 | -594.5918 | -3.7022 | -3.6221 | |
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| 0.4271 | 0.52 | 500 | 0.4441 | -2.0549 | -3.2181 | 0.7840 | 1.1631 | -652.2027 | -591.3006 | -3.8189 | -3.7408 | |
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| 0.4181 | 0.63 | 600 | 0.4366 | -1.9876 | -3.1678 | 0.7760 | 1.1802 | -647.1777 | -584.5698 | -3.7950 | -3.7170 | |
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| 0.4 | 0.73 | 700 | 0.4317 | -2.1647 | -3.3521 | 0.7640 | 1.1874 | -665.6046 | -602.2762 | -3.8739 | -3.7970 | |
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| 0.4123 | 0.84 | 800 | 0.4291 | -2.2039 | -3.4491 | 0.7680 | 1.2453 | -675.3075 | -606.1934 | -3.8606 | -3.7827 | |
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| 0.4394 | 0.94 | 900 | 0.4292 | -2.1325 | -3.3633 | 0.7680 | 1.2308 | -666.7250 | -599.0574 | -3.8777 | -3.8001 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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