learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
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: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3749	0.2697	1000	0.3099	0.9149	0.9174
0.2804	0.5394	2000	0.2330	0.9371	0.9305
0.2672	0.8091	3000	0.2369	0.9391	0.9339
0.2248	1.0787	4000	0.2295	0.9427	0.9406
0.1942	1.3484	5000	0.2244	0.9452	0.9422
0.1873	1.6181	6000	0.2310	0.9423	0.9393
0.1768	1.8878	7000	0.2155	0.9469	0.9450
0.1443	2.1575	8000	0.2295	0.9454	0.9449
0.1198	2.4272	9000	0.2295	0.9484	0.9474
0.1238	2.6969	10000	0.2278	0.9479	0.9469
0.1166	2.9666	11000	0.2307	0.9479	0.9467

Wiebke/task2_flausch_classification_gbert-large_span_classifier_with_nonspan

task2_flausch_classification_gbert-large_span_classifier_with_nonspan