judicial-summarization-llama-3-finetuned_mildsum_FL

This model is a fine-tuned version of unsloth/llama-3-8b-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.7972

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: 8
• seed: 3407
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 5
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss
1.3073	0.9991	273	1.4746
1.3533	1.9982	546	1.4690
1.1871	2.9973	819	1.5012
1.008	4.0	1093	1.5703
0.8119	4.9991	1366	1.6773
0.6565	5.9945	1638	1.7972

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1