llama3.2-1b-rumour-samples

• Loss: 2.0669
• Accuracy: 0.5449

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2.5e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 7788
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.47.0.dev0
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3