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dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs-adapter

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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: 0.5173
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+ - Rewards/chosen: -0.0019
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+ - Rewards/rejected: -0.7725
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+ - Rewards/accuracies: 0.7816
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+ - Rewards/margins: 0.7706
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+ - Logps/rejected: -233.5226
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+ - Logps/chosen: -214.1249
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+ - Logits/rejected: 0.3181
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+ - Logits/chosen: 0.2015
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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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+ | 0.6887 | 0.14 | 20 | 0.6767 | 0.0030 | -0.0331 | 0.6341 | 0.0361 | -226.1282 | -214.0752 | 0.2238 | 0.1343 |
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+ | 0.6472 | 0.27 | 40 | 0.6171 | 0.0141 | -0.1710 | 0.7639 | 0.1852 | -227.5079 | -213.9642 | 0.2464 | 0.1508 |
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+ | 0.5759 | 0.41 | 60 | 0.5584 | 0.0123 | -0.4023 | 0.7808 | 0.4146 | -229.8206 | -213.9829 | 0.2774 | 0.1736 |
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+ | 0.526 | 0.54 | 80 | 0.5326 | 0.0036 | -0.5790 | 0.7816 | 0.5826 | -231.5877 | -214.0700 | 0.2983 | 0.1884 |
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+ | 0.4963 | 0.68 | 100 | 0.5225 | 0.0020 | -0.6964 | 0.7825 | 0.6984 | -232.7611 | -214.0853 | 0.3131 | 0.1986 |
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+ | 0.4977 | 0.81 | 120 | 0.5188 | -0.0025 | -0.7533 | 0.7816 | 0.7508 | -233.3300 | -214.1302 | 0.3162 | 0.2002 |
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+ | 0.4818 | 0.95 | 140 | 0.5173 | -0.0019 | -0.7725 | 0.7816 | 0.7706 | -233.5226 | -214.1249 | 0.3181 | 0.2015 |
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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+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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