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Luggi/
task2_small

Name: task2_small
Rating: 2.5 (5 reviews)

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task2_small

This model is a fine-tuned version of distilbert/distilbert-base-german-cased on the None dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
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: 10

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0329	1.0	2359	0.0386	0.8098	0.8163	0.8130	0.9870
0.0245	2.0	4718	0.0356	0.8210	0.8551	0.8377	0.9888
0.0158	3.0	7077	0.0401	0.8426	0.8551	0.8488	0.9887
0.0118	4.0	9436	0.0417	0.8144	0.8664	0.8396	0.9885
0.0093	5.0	11795	0.0434	0.8470	0.8522	0.8496	0.9889
0.0063	6.0	14154	0.0472	0.8548	0.8580	0.8564	0.9891
0.0054	7.0	16513	0.0484	0.8450	0.8680	0.8564	0.9893
0.0049	8.0	18872	0.0492	0.8398	0.8693	0.8543	0.9894
0.0033	9.0	21231	0.0502	0.8397	0.8709	0.8550	0.9894
0.003	10.0	23590	0.0507	0.8401	0.8712	0.8554	0.9894