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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-2e-5
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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/a5eg2ijs)
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+ # Mistral-7B-Instruct-v0.2-MI-2e-5
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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: 1.5846
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+ - Rewards/chosen: -0.8695
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+ - Rewards/rejected: -0.9117
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+ - Rewards/accuracies: 0.5559
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+ - Rewards/margins: 0.0422
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+ - Logps/rejected: -0.9117
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+ - Logps/chosen: -0.8695
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+ - Logits/rejected: -2.8388
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+ - Logits/chosen: -2.8404
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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: 2e-05
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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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+ | 1.5218 | 0.8573 | 400 | 1.5846 | -0.8695 | -0.9117 | 0.5559 | 0.0422 | -0.9117 | -0.8695 | -2.8388 | -2.8404 |
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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_rewards/accuracies": 0.5598404407501221,
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+ "eval_rewards/margins": 0.04310305044054985,
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+ "eval_rewards/rejected": -0.9005469679832458,
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+ "eval_runtime": 436.1865,
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+ "eval_samples": 2994,
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+ "eval_samples_per_second": 6.864,
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+ "eval_steps_per_second": 0.431,
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+ "total_flos": 0.0,
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+ "train_loss": 1.5861326811651304,
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+ "train_runtime": 19371.3426,
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+ "train_samples": 59720,
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+ "train_samples_per_second": 3.083,
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+ "train_steps_per_second": 0.024
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+ }
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+ "eval_steps_per_second": 0.431
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