Llama-3-8B-Summarization-QLoRa

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the scitldr dataset. It achieves the following results on the evaluation set:

• Loss: 2.4051

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.226	0.5020	500	2.3232
2.2207	1.0040	1000	2.3130
1.6901	1.5060	1500	2.4051

Framework versions

• PEFT 0.10.0
• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1