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	Model Preparation Time	Accuracy	F1
0.2996	0.2822	500	0.2523	0.0033	0.9013	0.9023
0.2518	0.5643	1000	0.2112	0.0033	0.9228	0.9226
0.2269	0.8465	1500	0.2354	0.0033	0.9286	0.9278
0.1999	1.1287	2000	0.2223	0.0033	0.9330	0.9328
0.1669	1.4108	2500	0.2491	0.0033	0.9270	0.9275
0.1624	1.6930	3000	0.2328	0.0033	0.9318	0.9314
0.1557	1.9752	3500	0.2073	0.0033	0.9328	0.9325
0.1043	2.2573	4000	0.3011	0.0033	0.9340	0.9336
0.1103	2.5395	4500	0.2702	0.0033	0.9350	0.9348
0.109	2.8217	5000	0.2680	0.0033	0.9340	0.9339

Wiebke/results_flausch_classification_bert-base-german-cased_comment

results_flausch_classification_bert-base-german-cased_comment