learning_rate: 5e-05
train_batch_size: 64
eval_batch_size: 16
seed: 13
gradient_accumulation_steps: 8
total_train_batch_size: 512
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Auc
No log	1.0	71	0.3875	0.7164	0.8763	0.5741	0.6937	0.8758
No log	2.0	142	0.3601	0.8029	0.7437	0.9881	0.8487	0.8898
No log	3.0	213	0.3846	0.8026	0.7449	0.9843	0.8480	0.8906
No log	4.0	284	0.3749	0.8035	0.7458	0.9843	0.8486	0.8912
No log	5.0	355	0.3739	0.8050	0.7434	0.9948	0.8509	0.8927
No log	6.0	426	0.3768	0.8055	0.7452	0.9913	0.8508	0.8938
No log	7.0	497	0.3784	0.8064	0.7673	0.9386	0.8444	0.8941
0.3565	8.0	568	0.3834	0.8071	0.7653	0.9450	0.8457	0.8942

reichenbach/deberta-toxic-reward-grpo2

deberta-toxic-reward-grpo2