End of training
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README.md
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---
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library_name: peft
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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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model-index:
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- name: Llama-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V4
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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_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V4
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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: 0.6849
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- Rewards/chosen: -1.3255
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- Rewards/rejected: -1.6674
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- Rewards/accuracies: 0.5
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- Rewards/margins: 0.3419
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- Logps/rejected: -134.9012
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- Logps/chosen: -95.5139
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- Logits/rejected: 0.0033
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- Logits/chosen: 0.1072
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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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| 0.7204 | 0.3043 | 63 | 0.6808 | 0.0801 | 0.0519 | 0.7000 | 0.0281 | -117.7079 | -81.4587 | 0.4903 | 0.5915 |
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| 0.6989 | 0.6087 | 126 | 0.6930 | 0.0550 | 0.0726 | 0.6000 | -0.0176 | -117.5013 | -81.7093 | 0.4748 | 0.5762 |
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| 0.6896 | 0.9130 | 189 | 0.6579 | 0.1170 | 0.0536 | 0.5 | 0.0633 | -117.6909 | -81.0896 | 0.4569 | 0.5574 |
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| 0.3332 | 1.2174 | 252 | 0.6831 | -0.2141 | -0.2394 | 0.5 | 0.0253 | -120.6211 | -84.4000 | 0.3842 | 0.4834 |
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| 0.3687 | 1.5217 | 315 | 0.7069 | -0.6436 | -0.7406 | 0.5 | 0.0970 | -125.6332 | -88.6952 | 0.2816 | 0.3799 |
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| 0.2083 | 1.8261 | 378 | 0.6389 | -0.4156 | -0.5567 | 0.5 | 0.1411 | -123.7943 | -86.4158 | 0.2329 | 0.3317 |
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| 0.1191 | 2.1304 | 441 | 0.6451 | -0.8600 | -1.1248 | 0.5 | 0.2648 | -129.4748 | -90.8590 | 0.1067 | 0.2079 |
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| 0.1435 | 2.4348 | 504 | 0.6878 | -1.2620 | -1.5788 | 0.5 | 0.3168 | -134.0153 | -94.8793 | 0.0284 | 0.1320 |
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| 0.0848 | 2.7391 | 567 | 0.6849 | -1.3255 | -1.6674 | 0.5 | 0.3419 | -134.9012 | -95.5139 | 0.0033 | 0.1072 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.45.2
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- Pytorch 2.4.0+cu121
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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