deberta-v3-large-ft-icar-a-v0.10

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown 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: 3e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 3
total_train_batch_size: 3
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: 50

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
2.5523	1.0	871	0.6494	0.8683	0.8773	0.8534	0.8630
1.8228	2.0	1742	0.7068	0.8897	0.9008	0.8642	0.8751
1.4126	3.0	2613	0.6934	0.9005	0.8904	0.8965	0.8927
1.0964	4.0	3484	0.6747	0.9158	0.9111	0.9062	0.9082
0.8857	5.0	4355	0.8318	0.8989	0.8926	0.8980	0.8939
0.6865	6.0	5226	0.8226	0.9066	0.9050	0.8958	0.8996
0.5458	7.0	6097	0.7935	0.9158	0.9105	0.9089	0.9090
0.5311	8.0	6968	0.8565	0.9051	0.9062	0.8928	0.8982
0.3778	9.0	7839	0.8764	0.9158	0.9096	0.9096	0.9092
0.3385	10.0	8710	0.9250	0.9005	0.8790	0.9024	0.8897
0.226	11.0	9581	0.9597	0.9066	0.9104	0.8892	0.8979
0.2004	12.0	10452	1.0016	0.9127	0.9131	0.9083	0.9101
0.1238	13.0	11323	0.9480	0.9173	0.9147	0.9119	0.9126
0.138	14.0	12194	0.9453	0.9127	0.9080	0.9023	0.9045
0.1447	15.0	13065	1.0570	0.8943	0.8884	0.8996	0.8917
0.149	16.0	13936	1.1390	0.8989	0.8953	0.8846	0.8889
0.1106	17.0	14807	1.1037	0.9051	0.8952	0.8976	0.8960
0.0848	18.0	15678	1.0446	0.9066	0.9045	0.9071	0.9048
0.0556	19.0	16549	1.1846	0.9035	0.9052	0.8954	0.8997