learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: 1
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1372	0.1082	500	0.0982	0.9631	0.9638
0.0362	0.2164	1000	0.0379	0.9891	0.9890
0.037	0.3246	1500	0.0409	0.9884	0.9884
0.0325	0.4328	2000	0.0287	0.9919	0.9918
0.0222	0.5410	2500	0.0262	0.9943	0.9943
0.0222	0.6492	3000	0.0209	0.9945	0.9944
0.0218	0.7575	3500	0.0494	0.9879	0.9879
0.019	0.8657	4000	0.0198	0.9950	0.9949
0.0226	0.9739	4500	0.0228	0.9940	0.9939

XOmar/ai_vs_human_detector_deberta_v3_robust

ai_vs_human_detector_deberta_v3_robust