phi3-pruned-distilled-from-logits_all_med

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phi3-pruned-distilled-from-logits_all_med

This model is a fine-tuned version of olusegunola/phi3-pruned-layer-struct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 3.1225
• Ce Loss: 2.2006
• Kl Loss: 4.1091

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: 0.0002
• train_batch_size: 20
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 320
• optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 12

Training results

Framework versions

• PEFT 0.17.1
• Transformers 4.56.1
• Pytorch 2.8.0+cu128
• Datasets 3.2.0
• Tokenizers 0.22.0