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README.md ADDED
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+ ---
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+ library_name: transformers
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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-armorm
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+ model-index:
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+ - name: llama-3-8b-instruct-gapo-v2-rougeL-beta10-gamma0.3-lr1.0e-6-scale-log
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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-gapo-v2-rougeL-beta10-gamma0.3-lr1.0e-6-scale-log
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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-armorm dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2328
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+ - Rewards/chosen: -17.3682
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+ - Rewards/rejected: -23.0181
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+ - Rewards/accuracies: 0.8415
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+ - Rewards/margins: 5.6500
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+ - Logps/rejected: -2.3018
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+ - Logps/chosen: -1.7368
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+ - Logits/rejected: -1.3790
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+ - Logits/chosen: -1.3691
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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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+ | 1.2091 | 0.8550 | 400 | 1.2328 | -17.3682 | -23.0181 | 0.8415 | 5.6500 | -2.3018 | -1.7368 | -1.3790 | -1.3691 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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+ "epoch": 0.9982631930527722,
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+ "eval_loss": 1.228195309638977,
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+ "eval_rewards/accuracies": 0.8414633870124817,
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+ "eval_rewards/chosen": -17.612468719482422,
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+ "eval_rewards/margins": 5.710038185119629,
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+ "eval_rewards/rejected": -23.322505950927734,
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+ "eval_runtime": 87.9064,
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+ "eval_samples": 1961,
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+ "eval_samples_per_second": 22.308,
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+ "eval_steps_per_second": 1.399,
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+ "total_flos": 0.0,
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+ "train_loss": 1.8326820045773426,
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+ "train_runtime": 11496.4274,
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+ "train_samples": 59876,
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+ "train_samples_per_second": 5.208,
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+ "train_steps_per_second": 0.041
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+ }
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+ "vocab_size": 128256
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+ }
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