Model save
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README.md
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@@ -4,7 +4,6 @@ license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: llama3-1_8b_4o_annotated_aops
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# llama3-1_8b_4o_annotated_aops
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size:
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 32
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- total_train_batch_size: 96
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- total_eval_batch_size: 256
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- llama-factory
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- generated_from_trainer
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model-index:
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- name: llama3-1_8b_4o_annotated_aops
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# llama3-1_8b_4o_annotated_aops
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on an unknown dataset.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 32
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- gradient_accumulation_steps: 3
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- total_train_batch_size: 96
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- total_eval_batch_size: 256
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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