End of training
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README.md
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---
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base_model: meta-llama/Llama-2-7b-hf
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library_name: peft
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license: llama2
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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: Llama-2-7b-hf-DPO-LookAhead5_FullEval_TTree1.4_TLoop0.7_TEval0.2_V2.0
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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-LookAhead5_FullEval_TTree1.4_TLoop0.7_TEval0.2_V2.0
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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: 0.9728
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- Rewards/chosen: -2.0556
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- Rewards/rejected: -1.8953
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- Rewards/accuracies: 0.4167
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- Rewards/margins: -0.1602
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- Logps/rejected: -146.9038
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- Logps/chosen: -163.5856
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- Logits/rejected: -0.8198
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- Logits/chosen: -0.8110
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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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| 0.6766 | 0.2994 | 78 | 0.7200 | 0.0401 | 0.0730 | 0.4167 | -0.0329 | -127.2202 | -142.6290 | -0.3528 | -0.3393 |
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| 0.6875 | 0.5988 | 156 | 0.6657 | -0.4080 | -0.4881 | 0.5833 | 0.0801 | -132.8311 | -147.1099 | -0.3720 | -0.3575 |
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| 0.7999 | 0.8983 | 234 | 0.6842 | -0.3659 | -0.4094 | 0.6667 | 0.0435 | -132.0449 | -146.6892 | -0.3674 | -0.3517 |
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| 0.4879 | 1.1977 | 312 | 0.6694 | -0.2237 | -0.2979 | 0.4167 | 0.0742 | -130.9293 | -145.2672 | -0.3979 | -0.3821 |
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| 0.6233 | 1.4971 | 390 | 0.6523 | -0.9992 | -1.1797 | 0.5 | 0.1804 | -139.7471 | -153.0225 | -0.5012 | -0.4885 |
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| 0.4034 | 1.7965 | 468 | 0.7021 | -0.9141 | -1.0257 | 0.4167 | 0.1116 | -138.2080 | -152.1710 | -0.4511 | -0.4394 |
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| 0.1778 | 2.0960 | 546 | 0.7896 | -1.2322 | -1.2047 | 0.4167 | -0.0275 | -139.9971 | -155.3521 | -0.5752 | -0.5642 |
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| 0.2732 | 2.3954 | 624 | 0.9364 | -1.8694 | -1.7281 | 0.4167 | -0.1412 | -145.2318 | -161.7236 | -0.7728 | -0.7633 |
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| 0.1812 | 2.6948 | 702 | 0.9683 | -2.0710 | -1.9135 | 0.4167 | -0.1575 | -147.0860 | -163.7400 | -0.8137 | -0.8049 |
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| 0.1798 | 2.9942 | 780 | 0.9728 | -2.0556 | -1.8953 | 0.4167 | -0.1602 | -146.9038 | -163.5856 | -0.8198 | -0.8110 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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