learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 128
total_eval_batch_size: 128
optimizer: Use 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: 10.0

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0343	1.0	902	0.2095	0.9441	0.0	0.0	0.0
0.0344	2.0	1804	0.2093	0.9441	0.0	0.0	0.0
0.0368	3.0	2706	0.2190	0.9441	0.0	0.0	0.0
0.0396	4.0	3608	0.2225	0.9441	0.0	0.0	0.0
0.0335	5.0	4510	0.2161	0.9441	0.0	0.0	0.0
0.0307	6.0	5412	0.2188	0.9443	0.0105	0.75	0.0053
0.0222	7.0	6314	0.2325	0.9422	0.0958	0.3827	0.0548
0.0223	8.0	7216	0.2335	0.9409	0.1601	0.3904	0.1007
0.0173	9.0	8118	0.2529	0.9333	0.2268	0.3225	0.1749
0.0142	10.0	9020	0.2558	0.9270	0.2310	0.2810	0.1961

YWZBrandon/wikidyk-scope-clf-deberta-v3-large-temporal_10_clusters

wikidyk-scope-clf-deberta-v3-large-temporal_10_clusters