mcmaster-llama3-1b-full-pt

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the mcmaster dataset. It achieves the following results on the evaluation set:

• Loss: 0.0319

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• 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: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.3821	0.7436	500	0.3760
0.1018	1.4876	1000	0.1019
0.0376	2.2316	1500	0.0510
0.0267	2.9753	2000	0.0338
0.0118	3.7193	2500	0.0310
0.0055	4.4633	3000	0.0320

Framework versions

• Transformers 4.46.1
• Pytorch 2.5.1
• Datasets 3.1.0
• Tokenizers 0.20.3