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davidberenstein1957/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs

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README.md ADDED
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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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+ - trl
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+ - dpo
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+ - generated_from_trainer
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+ base_model: microsoft/phi-2
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+ model-index:
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+ - name: phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
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+ results: []
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+ ---
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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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+
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+ # phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
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+
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+ This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0972
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+ - Rewards/chosen: 0.2699
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+ - Rewards/rejected: -5.8246
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+ - Rewards/accuracies: 0.9623
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+ - Rewards/margins: 6.0944
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+ - Logps/rejected: -311.1872
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+ - Logps/chosen: -115.6127
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+ - Logits/rejected: 0.0766
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+ - Logits/chosen: 0.0242
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-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: 16
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 20
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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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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+ | 0.6805 | 0.06 | 20 | 0.6540 | 0.0096 | -0.0728 | 0.8367 | 0.0824 | -253.6698 | -118.2153 | 0.3760 | 0.3395 |
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+ | 0.5821 | 0.12 | 40 | 0.4977 | 0.0383 | -0.4385 | 0.9199 | 0.4768 | -257.3268 | -117.9285 | 0.3836 | 0.3356 |
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+ | 0.4163 | 0.19 | 60 | 0.3225 | 0.0641 | -1.1656 | 0.9257 | 1.2298 | -264.5979 | -117.6701 | 0.3836 | 0.3192 |
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+ | 0.275 | 0.25 | 80 | 0.2245 | 0.0476 | -2.1180 | 0.9316 | 2.1656 | -274.1212 | -117.8351 | 0.3399 | 0.2698 |
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+ | 0.1808 | 0.31 | 100 | 0.1771 | -0.0012 | -3.2019 | 0.9366 | 3.2007 | -284.9609 | -118.3238 | 0.2615 | 0.1964 |
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+ | 0.1405 | 0.37 | 120 | 0.1528 | 0.0185 | -4.0396 | 0.9425 | 4.0581 | -293.3371 | -118.1262 | 0.1983 | 0.1407 |
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+ | 0.1121 | 0.44 | 140 | 0.1389 | 0.0285 | -4.6518 | 0.9471 | 4.6802 | -299.4591 | -118.0267 | 0.1493 | 0.0980 |
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+ | 0.1544 | 0.5 | 160 | 0.1289 | 0.0745 | -4.9025 | 0.9506 | 4.9771 | -301.9670 | -117.5659 | 0.1257 | 0.0785 |
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+ | 0.1594 | 0.56 | 180 | 0.1204 | 0.1435 | -4.8770 | 0.9561 | 5.0205 | -301.7119 | -116.8765 | 0.1168 | 0.0696 |
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+ | 0.0988 | 0.62 | 200 | 0.1136 | 0.1830 | -5.1569 | 0.9576 | 5.3400 | -304.5108 | -116.4809 | 0.1078 | 0.0579 |
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+ | 0.1141 | 0.68 | 220 | 0.1080 | 0.2052 | -5.4532 | 0.9580 | 5.6584 | -307.4731 | -116.2591 | 0.0962 | 0.0460 |
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+ | 0.0943 | 0.75 | 240 | 0.1037 | 0.2326 | -5.6061 | 0.9592 | 5.8387 | -309.0026 | -115.9850 | 0.0913 | 0.0393 |
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+ | 0.1108 | 0.81 | 260 | 0.1008 | 0.2500 | -5.7399 | 0.9607 | 5.9900 | -310.3409 | -115.8109 | 0.0827 | 0.0316 |
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+ | 0.1088 | 0.87 | 280 | 0.0987 | 0.2677 | -5.7068 | 0.9619 | 5.9745 | -310.0096 | -115.6346 | 0.0825 | 0.0301 |
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+ | 0.0741 | 0.93 | 300 | 0.0975 | 0.2701 | -5.7873 | 0.9623 | 6.0574 | -310.8145 | -115.6102 | 0.0788 | 0.0261 |
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+ | 0.1059 | 1.0 | 320 | 0.0972 | 0.2699 | -5.8246 | 0.9623 | 6.0944 | -311.1872 | -115.6127 | 0.0766 | 0.0242 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.7.1
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+ - Transformers 4.37.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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