learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
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: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Threatening Accuracy	Threatening F1	Threatening Precision	Threatening Recall	Conciliatory Accuracy	Conciliatory F1	Conciliatory Precision	Conciliatory Recall	Formal Accuracy	Formal F1	Formal Precision	Formal Recall	Persuasive Accuracy	Persuasive F1	Persuasive Precision	Persuasive Recall	Overall Accuracy
0.6671	1.0	27	0.6366	0.4595	0.0909	1.0	0.0476	0.6216	0.2632	0.5	0.1786	0.7297	0.8438	0.7297	1.0	0.6892	0.7723	0.6842	0.8864	0.625
0.6124	2.0	54	0.5715	0.4865	0.1739	1.0	0.0952	0.6351	0.5424	0.5161	0.5714	0.8919	0.9298	0.8833	0.9815	0.7027	0.78	0.6964	0.8864	0.6791
0.531	3.0	81	0.5137	0.7297	0.7222	0.8667	0.6190	0.6892	0.6102	0.5806	0.6429	0.9730	0.9811	1.0	0.9630	0.6892	0.7294	0.7561	0.7045	0.7703
0.4845	4.0	108	0.4720	0.7568	0.7568	0.875	0.6667	0.7703	0.7385	0.6486	0.8571	0.9730	0.9811	1.0	0.9630	0.7027	0.7556	0.7391	0.7727	0.8007
0.4287	5.0	135	0.4524	0.7162	0.7273	0.8	0.6667	0.7432	0.6984	0.6286	0.7857	0.9730	0.9811	1.0	0.9630	0.6892	0.7294	0.7561	0.7045	0.7804

bulpara/kanuni_model

kanuni_model