CS221-deberta-v3-base-finetuned-augmentation

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4444	1.0	180	0.4238	0.5147	0.6834	0.3621
0.3212	2.0	360	0.3233	0.7223	0.7933	0.5024
0.2397	3.0	540	0.2473	0.8341	0.8798	0.6442
0.1506	4.0	720	0.2095	0.8683	0.9076	0.7262
0.0987	5.0	900	0.2038	0.8838	0.9122	0.7498
0.0659	6.0	1080	0.1869	0.9068	0.9311	0.8151
0.0432	7.0	1260	0.2043	0.9027	0.9253	0.8096
0.029	8.0	1440	0.1907	0.9135	0.9337	0.8270
0.02	9.0	1620	0.1930	0.9240	0.9423	0.8520
0.0128	10.0	1800	0.2234	0.9180	0.9402	0.8381
0.0115	11.0	1980	0.2132	0.9185	0.9395	0.8409
0.01	12.0	2160	0.2166	0.9249	0.9440	0.8520
0.0055	13.0	2340	0.2182	0.9267	0.9438	0.8568
0.0057	14.0	2520	0.2263	0.9245	0.9445	0.8562
0.0041	15.0	2700	0.2246	0.9254	0.9464	0.8555
0.0043	16.0	2880	0.2285	0.9258	0.9451	0.8548