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README.md ADDED
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+ ---
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+ base_model: Minbyul/llama2-7b-wo-kqa_golden-sft
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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: llama2-7b-dpo-full-sft-wo-kqa_golden
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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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+ # llama2-7b-dpo-full-sft-wo-kqa_golden
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+
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+ This model is a fine-tuned version of [Minbyul/llama2-7b-wo-kqa_golden-sft](https://huggingface.co/Minbyul/llama2-7b-wo-kqa_golden-sft) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3024
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+ - Rewards/chosen: -0.0879
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+ - Rewards/rejected: -1.9222
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+ - Rewards/accuracies: 0.9500
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+ - Rewards/margins: 1.8343
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+ - Logps/rejected: -748.6945
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+ - Logps/chosen: -311.0383
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+ - Logits/rejected: -0.5637
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+ - Logits/chosen: -0.7827
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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-07
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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+ - total_eval_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: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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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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+ | 0.2497 | 0.74 | 100 | 0.3024 | -0.0879 | -1.9222 | 0.9500 | 1.8343 | -748.6945 | -311.0383 | -0.5637 | -0.7827 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.2
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+ - Datasets 2.14.6
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+ - Tokenizers 0.15.2
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+ "train_samples_per_second": 4.489,
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+ "train_steps_per_second": 0.07
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+ }
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+ "temperature": 0.6,
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+ "top_p": 0.9,
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+ "transformers_version": "4.39.0.dev0"
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+ }
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