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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: alignment-handbook/zephyr-7b-sft-full
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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: zephyr-7b-dpo-full-gpt_consistent-3
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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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+ # zephyr-7b-dpo-full-gpt_consistent-3
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+
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+ This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4898
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+ - Rewards/chosen: -0.9477
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+ - Rewards/rejected: -1.9210
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+ - Rewards/accuracies: 0.7543
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+ - Rewards/margins: 0.9733
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+ - Logps/rejected: -438.6234
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+ - Logps/chosen: -379.8649
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+ - Logits/rejected: 2.2425
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+ - Logits/chosen: 0.9259
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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: 55
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 64
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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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+ | 0.5718 | 0.2294 | 100 | 0.5525 | -0.3811 | -0.9418 | 0.6940 | 0.5607 | -340.7015 | -323.2031 | -1.1398 | -1.3666 |
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+ | 0.5281 | 0.4587 | 200 | 0.5102 | -0.6195 | -1.4237 | 0.7457 | 0.8042 | -388.8913 | -347.0378 | 1.0061 | -0.1205 |
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+ | 0.5213 | 0.6881 | 300 | 0.4939 | -0.9485 | -1.8771 | 0.7543 | 0.9286 | -434.2354 | -379.9385 | 1.7281 | 0.3985 |
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+ | 0.5037 | 0.9174 | 400 | 0.4898 | -0.9477 | -1.9210 | 0.7543 | 0.9733 | -438.6234 | -379.8649 | 2.2425 | 0.9259 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0.dev0
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "train_samples_per_second": 4.936,
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+ "train_steps_per_second": 0.039
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+ }
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