Johhny1201/llama3.2_1b_med_QA_2

medicalQA_1b_2

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the MedQA2 and the Med_int_data datasets. It achieves the following results on the evaluation set:

• Loss: 1.2446

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss
1.3452	0.6254	500	1.5974
0.8293	1.2508	1000	1.3727
0.7086	1.8762	1500	1.2465

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.1+cu124
• Datasets 2.21.0
• Tokenizers 0.20.3