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README.md ADDED
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+ ---
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+ license: llama3
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+ base_model: meta-llama/Meta-Llama-3-8B-Instruct
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - princeton-nlp/llama3-ultrafeedback
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+ model-index:
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+ - name: llama-3-8b-instruct-cpo-beta-0.1
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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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+ # llama-3-8b-instruct-cpo-beta-0.1
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+
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+ This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the princeton-nlp/llama3-ultrafeedback dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3274
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+ - Rewards/chosen: -13.1885
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+ - Rewards/rejected: -14.3989
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+ - Rewards/accuracies: 0.7016
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+ - Rewards/margins: 1.2104
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+ - Logps/rejected: -143.9887
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+ - Logps/chosen: -131.8848
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+ - Logits/rejected: 0.2135
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+ - Logits/chosen: 0.1708
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+ - Nll Loss: 0.3287
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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: 16
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+ - gradient_accumulation_steps: 4
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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 | Nll Loss |
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+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
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+ | 1.2968 | 0.8547 | 400 | 1.3274 | -13.1885 | -14.3989 | 0.7016 | 1.2104 | -143.9887 | -131.8848 | 0.2135 | 0.1708 | 0.3287 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+rocm6.0
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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+ {
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+ "eval_loss": 1.3258469104766846,
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+ "eval_nll_loss": 0.3315570652484894,
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+ "eval_rewards/accuracies": 0.7177419066429138,
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+ "eval_rewards/chosen": -13.3015718460083,
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+ "eval_rewards/margins": 1.216615080833435,
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+ "eval_rewards/rejected": -14.518187522888184,
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+ "eval_runtime": 102.7641,
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+ "eval_samples": 1961,
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+ "eval_samples_per_second": 19.083,
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+ "eval_steps_per_second": 0.302,
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+ "total_flos": 0.0,
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+ "train_loss": 1.4382328207676227,
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+ "train_runtime": 9608.0854,
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+ "train_samples": 59876,
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+ "train_samples_per_second": 6.232,
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+ "train_steps_per_second": 0.049
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+ }
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+ "vocab_size": 128256
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