distilbert-text-classifier

This model is a fine-tuned version of distilbert-base-uncased 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: 5e-05
train_batch_size: 32
eval_batch_size: 64
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: linear
num_epochs: 40

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3169	1.0	632	0.2758	0.9174
0.1195	2.0	1264	0.2899	0.9218
0.092	3.0	1896	0.3103	0.9274
0.0951	4.0	2528	0.3161	0.9335
0.0435	5.0	3160	0.3640	0.9336
0.0294	6.0	3792	0.4195	0.9310
0.0444	7.0	4424	0.4745	0.9286
0.001	8.0	5056	0.4672	0.9355
0.0577	9.0	5688	0.5112	0.9282
0.0003	10.0	6320	0.4807	0.9362
0.0135	11.0	6952	0.5246	0.9319
0.0026	12.0	7584	0.5371	0.9345
0.0012	13.0	8216	0.5445	0.9351
0.0023	14.0	8848	0.5788	0.9335
0.0006	15.0	9480	0.5707	0.9335
0.0018	16.0	10112	0.5424	0.9375
0.0034	17.0	10744	0.5418	0.9345
0.0004	18.0	11376	0.5673	0.9389
0.0001	19.0	12008	0.5738	0.9349
0.01	20.0	12640	0.5651	0.9389
0.0011	21.0	13272	0.6153	0.9339
0.0224	22.0	13904	0.6216	0.9356
0.0001	23.0	14536	0.5976	0.9353
0.0417	24.0	15168	0.6134	0.9329
0.0	25.0	15800	0.5920	0.9377
0.0	26.0	16432	0.6247	0.9377
0.0	27.0	17064	0.6435	0.9372
0.0	28.0	17696	0.7084	0.9320
0.0	29.0	18328	0.7095	0.9343
0.0	30.0	18960	0.6708	0.9362
0.0	31.0	19592	0.6704	0.9384
0.0	32.0	20224	0.6665	0.9383
0.0	33.0	20856	0.6910	0.9388
0.0	34.0	21488	0.6861	0.9375
0.0	35.0	22120	0.6714	0.9386
0.0	36.0	22752	0.6914	0.9397
0.0	37.0	23384	0.6756	0.9390
0.0	38.0	24016	0.6780	0.9390
0.0	39.0	24648	0.6751	0.9394
0.0	40.0	25280	0.6756	0.9395