End of training
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README.md
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---
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license: llama2
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base_model: meta-llama/Llama-2-7b-hf
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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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library_name: peft
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model-index:
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- name: Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V6
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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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# Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V6
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0184
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- Rewards/chosen: -1.6627
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- Rewards/rejected: -1.4611
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- Rewards/accuracies: 0.5
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- Rewards/margins: -0.2016
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- Logps/rejected: -142.2372
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- Logps/chosen: -159.6465
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- Logits/rejected: -0.2970
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- Logits/chosen: -0.3265
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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-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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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_steps: 10
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- num_epochs: 3
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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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| 0.6746 | 0.3012 | 75 | 0.6658 | 0.0862 | 0.0321 | 0.75 | 0.0541 | -127.3055 | -142.1577 | 0.1821 | 0.1663 |
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| 0.5925 | 0.6024 | 150 | 0.6506 | 0.1218 | 0.0304 | 0.5833 | 0.0914 | -127.3224 | -141.8020 | 0.1565 | 0.1401 |
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| 0.7335 | 0.9036 | 225 | 0.7279 | -0.0626 | -0.0395 | 0.5 | -0.0231 | -128.0216 | -143.6459 | 0.1275 | 0.1103 |
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| 0.6498 | 1.2048 | 300 | 0.7880 | -0.2917 | -0.2254 | 0.4167 | -0.0663 | -129.8807 | -145.9371 | 0.0678 | 0.0485 |
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| 0.386 | 1.5060 | 375 | 0.7303 | -0.2014 | -0.2339 | 0.5 | 0.0325 | -129.9658 | -145.0339 | 0.0325 | 0.0140 |
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| 0.2307 | 1.8072 | 450 | 0.8159 | -0.5206 | -0.4793 | 0.5 | -0.0412 | -132.4201 | -148.2257 | -0.0582 | -0.0797 |
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| 0.1034 | 2.1084 | 525 | 0.9133 | -1.0254 | -0.8918 | 0.4167 | -0.1335 | -136.5451 | -153.2736 | -0.2025 | -0.2290 |
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| 0.284 | 2.4096 | 600 | 1.0153 | -1.5972 | -1.3870 | 0.4167 | -0.2102 | -141.4962 | -158.9917 | -0.2790 | -0.3083 |
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| 0.0599 | 2.7108 | 675 | 1.0184 | -1.6627 | -1.4611 | 0.5 | -0.2016 | -142.2372 | -159.6465 | -0.2970 | -0.3265 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu121
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- Datasets 3.1.0
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- Tokenizers 0.19.1
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