learning_rate: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1 Macro	F1 Weighted
0.4592	1.0	90	0.2280	0.9356	0.8885	0.7440	0.7800	0.9283
0.1801	2.0	180	0.1823	0.9476	0.8617	0.8443	0.8523	0.9469
0.1221	3.0	270	0.1834	0.9482	0.8795	0.8359	0.8548	0.9467
0.1071	4.0	360	0.1868	0.9520	0.9086	0.8096	0.8447	0.9486
0.0817	5.0	450	0.2031	0.9526	0.8980	0.8393	0.8635	0.9508
0.065	6.0	540	0.2240	0.9501	0.8908	0.8084	0.8389	0.9469
0.0574	7.0	630	0.2219	0.9501	0.8625	0.8701	0.8662	0.9504
0.0481	8.0	720	0.2503	0.9469	0.8752	0.8266	0.8472	0.9451
0.0362	9.0	810	0.2489	0.9495	0.8822	0.8121	0.8392	0.9466
0.0319	10.0	900	0.2584	0.9501	0.8784	0.8413	0.8577	0.9488
0.0263	11.0	990	0.2774	0.9488	0.8800	0.8281	0.8498	0.9469
0.0199	12.0	1080	0.2790	0.9501	0.8780	0.8416	0.8577	0.9488
0.0114	13.0	1170	0.2955	0.9476	0.8733	0.8393	0.8546	0.9463
0.0126	14.0	1260	0.3105	0.9501	0.8953	0.8331	0.8586	0.9481
0.0125	15.0	1350	0.3147	0.9482	0.8773	0.8397	0.8564	0.9469
0.0106	16.0	1440	0.3247	0.9469	0.8861	0.8350	0.8567	0.9453
0.0065	17.0	1530	0.3419	0.9476	0.8751	0.8274	0.8476	0.9458
0.0072	18.0	1620	0.3406	0.9469	0.8933	0.8185	0.8475	0.9444
0.0058	19.0	1710	0.3389	0.9495	0.8904	0.8328	0.8566	0.9476
0.0064	20.0	1800	0.3362	0.9482	0.8854	0.8318	0.8543	0.9464

aiface/phobert-base_v2

phobert-base_v2