learning_rate: 0.0001
train_batch_size: 24
eval_batch_size: 48
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 96
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: polynomial
lr_scheduler_warmup_ratio: 0.06
num_epochs: 7
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
3.0764	1.0	64	1.6987	0.6210	0.5278	0.6210	0.5529
1.6258	2.0	128	1.3065	0.6845	0.6331	0.6845	0.6401
1.2496	3.0	192	1.1332	0.7113	0.6755	0.7113	0.6801
0.7597	4.0	256	1.0614	0.7435	0.7298	0.7435	0.7219
0.6033	5.0	320	1.0464	0.7565	0.7427	0.7565	0.7423
0.457	6.0	384	1.0559	0.7496	0.7399	0.7496	0.7383
0.3654	7.0	448	1.0642	0.7519	0.7393	0.7519	0.7395

Bukareszt/mwik-classifier-extended

mwik-classifier-ext