learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
0.6887	0.0889	500	0.6459
0.6096	0.1778	1000	0.6775
0.6015	0.2667	1500	0.6109
0.5830	0.3556	2000	0.5507
0.5903	0.4444	2500	0.5418
0.5977	0.5333	3000	0.5269
0.5592	0.6222	3500	0.5251
0.5307	0.7111	4000	0.5365
0.4979	0.8	4500	0.5297
0.4893	0.8889	5000	0.4966
0.5503	0.9778	5500	0.4785
0.4640	1.0667	6000	0.4970
0.4765	1.1556	6500	0.4951
0.4854	1.2444	7000	0.4848
0.4704	1.3333	7500	0.4708
0.4465	1.4222	8000	0.4798
0.4347	1.5111	8500	0.5201
0.4194	1.6	9000	0.4804
0.4528	1.6889	9500	0.4569
0.3792	1.7778	10000	0.4705
0.4289	1.8667	10500	0.4577
0.4470	1.9556	11000	0.4620
0.3964	2.0444	11500	0.4738
0.4094	2.1333	12000	0.4698
0.3436	2.2222	12500	0.4746
0.4208	2.3111	13000	0.4710
0.3772	2.4	13500	0.4821
0.4110	2.4889	14000	0.4608
0.3324	2.5778	14500	0.4774
0.4161	2.6667	15000	0.4563
0.4208	2.7556	15500	0.4611
0.3776	2.8444	16000	0.4609
0.4345	2.9333	16500	0.4579

vilfrid/sentinelle-sentiment-detector

sentinelle-sentiment-detector