Llama-3.1-8B-Instruct-INBioCR-sp-DAPT-ft-INBioCR_plants_QAV2

• Loss: 0.9310

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 0.0001
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Framework versions

• PEFT 0.18.0
• Transformers 4.57.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.22.1