learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 100
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.5833	1.0	31	0.5356	0.75	0.0	0.0	0.0
0.526	2.0	62	0.4851	0.75	0.0	0.0	0.0
0.4795	3.0	93	0.4745	0.7724	0.1644	1.0	0.0896
0.3989	4.0	124	0.3300	0.8657	0.6667	0.8780	0.5373
0.2827	5.0	155	0.3112	0.8657	0.7391	0.7183	0.7612
0.2006	6.0	186	0.2641	0.8955	0.7705	0.8545	0.7015
0.1357	7.0	217	0.3315	0.8881	0.7917	0.7403	0.8507
0.1251	8.0	248	0.4118	0.8433	0.7308	0.6404	0.8507
0.0643	9.0	279	0.4539	0.8918	0.7642	0.8393	0.7015
0.046	10.0	310	0.5066	0.8694	0.7518	0.7162	0.7910

enoubi/XLM-RoBERTa-Twitter-Indonesian-Sarcastic-Few-Shot

XLM-RoBERTa-Twitter-Indonesian-Sarcastic-Few-Shot