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--- |
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license: mit |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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- trl |
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- dpo |
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base_model: microsoft/phi-2 |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: phi-2-gpo-renew2-b0.001-0.5ultrafeedback-rank256-i1 |
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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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# phi-2-gpo-renew2-b0.001-0.5ultrafeedback-rank256-i1 |
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This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-renew2-b0.001-i0](https://huggingface.co/DUAL-GPO/phi-2-gpo-renew2-b0.001-i0) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0492 |
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- Rewards/chosen: 0.0680 |
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- Rewards/rejected: 0.0518 |
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- Rewards/accuracies: 0.5700 |
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- Rewards/margins: 0.0162 |
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- Logps/rejected: -1824.6278 |
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- Logps/chosen: -2148.4272 |
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- Logits/rejected: -0.2254 |
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- Logits/chosen: -0.2188 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_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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| 0.0519 | 0.05 | 100 | 0.0524 | 0.0326 | 0.0267 | 0.5255 | 0.0059 | -1849.7029 | -2183.7695 | -0.2520 | -0.2532 | |
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| 0.0379 | 0.1 | 200 | 0.0514 | 0.0434 | 0.0342 | 0.5390 | 0.0093 | -1842.2477 | -2172.9629 | -0.2760 | -0.2740 | |
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| 0.0425 | 0.16 | 300 | 0.0513 | 0.0344 | 0.0246 | 0.5630 | 0.0098 | -1851.8621 | -2182.0454 | -0.2899 | -0.2901 | |
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| 0.0522 | 0.21 | 400 | 0.0520 | 0.0818 | 0.0659 | 0.5250 | 0.0159 | -1810.5037 | -2134.5779 | -0.2777 | -0.2683 | |
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| 0.0559 | 0.26 | 500 | 0.0502 | 0.0610 | 0.0475 | 0.5625 | 0.0134 | -1828.8737 | -2155.4170 | -0.2991 | -0.2903 | |
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| 0.0546 | 0.31 | 600 | 0.0504 | 0.0493 | 0.0369 | 0.5525 | 0.0124 | -1839.5269 | -2167.1086 | -0.3840 | -0.3719 | |
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| 0.0443 | 0.37 | 700 | 0.0501 | 0.0527 | 0.0403 | 0.5670 | 0.0124 | -1836.1396 | -2163.6941 | -0.3238 | -0.3145 | |
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| 0.0583 | 0.42 | 800 | 0.0502 | 0.0559 | 0.0434 | 0.5625 | 0.0125 | -1833.0012 | -2160.5334 | -0.3079 | -0.2990 | |
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| 0.0432 | 0.47 | 900 | 0.0500 | 0.0872 | 0.0702 | 0.5485 | 0.0170 | -1806.2087 | -2129.1819 | -0.2529 | -0.2455 | |
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| 0.0538 | 0.52 | 1000 | 0.0496 | 0.0598 | 0.0468 | 0.5650 | 0.0129 | -1829.5831 | -2156.6528 | -0.2593 | -0.2565 | |
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| 0.0545 | 0.58 | 1100 | 0.0495 | 0.0923 | 0.0738 | 0.5560 | 0.0185 | -1802.5935 | -2124.1084 | -0.2394 | -0.2311 | |
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| 0.0481 | 0.63 | 1200 | 0.0495 | 0.0607 | 0.0467 | 0.5685 | 0.0140 | -1829.7306 | -2155.7429 | -0.2181 | -0.2147 | |
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| 0.0441 | 0.68 | 1300 | 0.0495 | 0.0567 | 0.0429 | 0.5690 | 0.0139 | -1833.5485 | -2159.6755 | -0.2202 | -0.2175 | |
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| 0.0524 | 0.73 | 1400 | 0.0496 | 0.0527 | 0.0389 | 0.5685 | 0.0138 | -1837.5038 | -2163.6599 | -0.2475 | -0.2422 | |
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| 0.0425 | 0.79 | 1500 | 0.0493 | 0.0621 | 0.0466 | 0.5675 | 0.0154 | -1829.7928 | -2154.3403 | -0.2335 | -0.2274 | |
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| 0.0387 | 0.84 | 1600 | 0.0492 | 0.0712 | 0.0545 | 0.5705 | 0.0167 | -1821.8909 | -2145.1594 | -0.2298 | -0.2230 | |
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| 0.0556 | 0.89 | 1700 | 0.0492 | 0.0673 | 0.0511 | 0.5675 | 0.0161 | -1825.2786 | -2149.1382 | -0.2259 | -0.2196 | |
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| 0.0519 | 0.94 | 1800 | 0.0492 | 0.0683 | 0.0521 | 0.5690 | 0.0162 | -1824.3348 | -2148.1096 | -0.2241 | -0.2176 | |
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| 0.05 | 0.99 | 1900 | 0.0492 | 0.0679 | 0.0518 | 0.5670 | 0.0162 | -1824.6459 | -2148.4578 | -0.2254 | -0.2187 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
