llm_checkpoints

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llm_checkpoints

This model is a fine-tuned version of microsoft/Phi-4-mini-instruct on the goals_finetune_train dataset. It achieves the following results on the evaluation set:

• Loss: 0.3068

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• total_eval_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 30
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• PEFT 0.18.1
• Transformers 4.51.3
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.21.4