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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: mistralai/Mistral-7B-Instruct-v0.2
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+ tags:
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+ - alignment_handbook-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - princeton-nlp/mistral-instruct-ultrafeedback
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+ model-index:
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+ - name: Mistral-7B-Instruct-v0.2-MI-1e-6
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tengxiao01/huggingface/runs/asrk9rw7)
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+ # Mistral-7B-Instruct-v0.2-MI-1e-6
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the princeton-nlp/mistral-instruct-ultrafeedback dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5092
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+ - Rewards/chosen: -0.5707
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+ - Rewards/rejected: -0.6483
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+ - Rewards/accuracies: 0.5931
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+ - Rewards/margins: 0.0775
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+ - Logps/rejected: -0.6483
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+ - Logps/chosen: -0.5707
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+ - Logits/rejected: -3.4481
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+ - Logits/chosen: -3.4530
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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-06
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+ - train_batch_size: 2
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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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+ - num_devices: 4
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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+ - total_eval_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: 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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+ | 1.46 | 0.8573 | 400 | 1.5092 | -0.5707 | -0.6483 | 0.5931 | 0.0775 | -0.6483 | -0.5707 | -3.4481 | -3.4530 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.19.1
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+ "eval_loss": 1.509045958518982,
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+ "eval_rewards/accuracies": 0.5890957713127136,
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+ "eval_rewards/chosen": -0.5745237469673157,
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+ "eval_rewards/margins": 0.07872254401445389,
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+ "eval_rewards/rejected": -0.6532463431358337,
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+ "eval_runtime": 434.8486,
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+ "eval_samples": 2994,
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+ "eval_samples_per_second": 6.885,
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+ "eval_steps_per_second": 0.432,
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+ "total_flos": 0.0,
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+ "train_loss": 1.5033698225226013,
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+ "train_runtime": 19350.3696,
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+ "train_samples": 59720,
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+ "train_samples_per_second": 3.086,
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+ "train_steps_per_second": 0.024
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+ }
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+ "eval_steps_per_second": 0.432
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+ }
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