openmathinstruct2-llama-3.1-8B-Instruct

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openmathinstruct2-llama-3.1-8B-Instruct

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the openmathinstruct2_cot_20k_train dataset. It achieves the following results on the evaluation set:

• Loss: 0.7514

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-06
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1.0

Training results

Framework versions

• Transformers 4.45.2
• Pytorch 2.3.0+cu121
• Datasets 2.21.0
• Tokenizers 0.20.1