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contemmcm/
b3e36b8ecaa0de9195fc36f8913303b8

Name: b3e36b8ecaa0de9195fc36f8913303b8
Rating: 2.5 (5 reviews)

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b3e36b8ecaa0de9195fc36f8913303b8

This model is a fine-tuned version of distilbert/distilbert-base-uncased-distilled-squad on the contemmcm/trec dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
num_epochs: 50

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro
No log	0	0	1.8271	0	0.7633	0.1021	0.0430
No log	1	170	1.6646	0.0078	0.9938	0.3583	0.1980
No log	2	340	1.5154	0.0156	1.0284	0.5333	0.4079
No log	3	510	1.1134	0.0312	1.1448	0.9021	0.7548
No log	4	680	0.5776	0.0625	1.2973	0.9104	0.7653
0.0547	5	850	0.2355	0.125	1.7117	0.9521	0.8007
0.0547	6	1020	0.2012	0.25	2.1348	0.9542	0.9309
0.2029	7	1190	0.2062	0.5	3.2885	0.9563	0.9313
0.141	8.0	1360	0.1672	1.0	5.5069	0.9625	0.9589
0.0709	9.0	1530	0.1640	1.0	5.4317	0.975	0.9776
0.0595	10.0	1700	0.1848	1.0	5.3818	0.9646	0.9432
0.0368	11.0	1870	0.1740	1.0	5.4152	0.9688	0.9647
0.0257	12.0	2040	0.3008	1.0	5.3703	0.9563	0.9349
0.0137	13.0	2210	0.2582	1.0	5.4157	0.9667	0.9567