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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: phi-2-gpo-test-longest-iter-random-1
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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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+ # phi-2-gpo-test-longest-iter-random-1
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0022
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+ - Rewards/chosen: 0.0010
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+ - Rewards/rejected: 0.0016
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+ - Rewards/accuracies: 0.4790
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+ - Rewards/margins: -0.0006
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+ - Logps/rejected: -278.5288
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+ - Logps/chosen: -306.2895
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+ - Logits/rejected: 0.0882
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+ - Logits/chosen: -0.0097
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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: 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: 4
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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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+ | 0.0016 | 1.6 | 100 | 0.0021 | 0.0005 | 0.0001 | 0.4910 | 0.0004 | -278.6740 | -306.3399 | 0.0933 | -0.0050 |
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+ | 0.0017 | 3.2 | 200 | 0.0022 | -0.0007 | -0.0006 | 0.4950 | -0.0001 | -278.7457 | -306.4609 | 0.0886 | -0.0095 |
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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 4.36.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.15.2
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