Llama-3.2-1B-Summarization-LoRa

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Llama-3.2-1B-Summarization-LoRa

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the scitldr dataset. It achieves the following results on the evaluation set:

• Loss: 2.5661

Model description

Fine-tuned (LoRa) Version of meta-llama/Llama-3.2-1B for Summarization of scientific documents

Intended uses & limitations

Summarization

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Framework versions

• PEFT 0.13.2
• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3