learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use adamw_torch 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: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
1.3459	1.0	360	0.7530	0.6667	0.6615
0.8291	2.0	720	0.4807	0.8021	0.7951
0.8198	3.0	1080	0.4037	0.8306	0.8255
0.6597	4.0	1440	0.4082	0.8292	0.8270
0.5621	5.0	1800	0.3817	0.8438	0.8410
0.5646	6.0	2160	0.3784	0.8472	0.8453
0.4532	7.0	2520	0.3879	0.8431	0.8401

msab97/LLama3-1B-finetuning

LLama3-1B-finetuning