Llama-3.1-8B-Instruct-JudicialSummarization-FinetuneLlama3.18b

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

• Loss: 6.4096

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: 2.5e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• 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
• lr_scheduler_warmup_steps: 5
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
6.4708	0.6887	500	6.4666
6.4187	1.3774	1000	6.4331
6.3747	2.0661	1500	6.4159
6.3408	2.7548	2000	6.4096

Framework versions

• PEFT 0.13.2
• Transformers 4.46.1
• Pytorch 2.4.0+cu121
• Datasets 3.0.1
• Tokenizers 0.20.1