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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-LookAhead-5_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_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: 1.2125 |
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- Rewards/chosen: -3.3104 |
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- Rewards/rejected: -2.9319 |
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- Rewards/accuracies: 0.4167 |
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- Rewards/margins: -0.3786 |
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- Logps/rejected: -192.9225 |
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- Logps/chosen: -170.2794 |
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- Logits/rejected: 0.1199 |
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- Logits/chosen: 0.1595 |
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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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| 0.6179 | 0.3027 | 79 | 0.7115 | -0.1031 | -0.0593 | 0.25 | -0.0438 | -164.1966 | -138.2057 | 0.5429 | 0.5748 | |
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| 0.6065 | 0.6054 | 158 | 0.7348 | -0.0751 | 0.0129 | 0.25 | -0.0879 | -163.4753 | -137.9259 | 0.5242 | 0.5565 | |
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| 0.621 | 0.9080 | 237 | 0.7932 | -0.0433 | 0.1366 | 0.5 | -0.1800 | -162.2375 | -137.6083 | 0.4932 | 0.5259 | |
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| 0.4714 | 1.2107 | 316 | 0.7928 | -0.6963 | -0.5927 | 0.5 | -0.1037 | -169.5308 | -144.1387 | 0.4698 | 0.5037 | |
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| 0.3829 | 1.5134 | 395 | 0.8637 | -1.6604 | -1.5528 | 0.3333 | -0.1075 | -179.1323 | -153.7787 | 0.3664 | 0.4026 | |
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| 0.3589 | 1.8161 | 474 | 0.9222 | -1.4397 | -1.1360 | 0.25 | -0.3037 | -174.9637 | -151.5720 | 0.3400 | 0.3770 | |
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| 0.2138 | 2.1188 | 553 | 0.9860 | -1.9991 | -1.6486 | 0.3333 | -0.3505 | -180.0903 | -157.1666 | 0.2605 | 0.2992 | |
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| 0.0437 | 2.4215 | 632 | 1.1781 | -3.1628 | -2.7961 | 0.4167 | -0.3666 | -191.5652 | -168.8030 | 0.1441 | 0.1838 | |
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| 0.1667 | 2.7241 | 711 | 1.2125 | -3.3104 | -2.9319 | 0.4167 | -0.3786 | -192.9225 | -170.2794 | 0.1199 | 0.1595 | |
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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 |
