EmoCentricSarcBERT27FebRstate100000AvgPadding

This model is a fine-tuned version of bert-base-cased 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
distributed_type: tpu
optimizer: Use OptimizerNames.ADAMW_TORCH_XLA 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	Accuracy	Precision	Recall	F1	Mcc	Roc Auc
0.3934	1.0	735	0.2922	0.8635	0.8272	0.8214	0.8243	0.7127	0.9441
0.2821	2.0	1470	0.2949	0.8763	0.8535	0.8240	0.8385	0.7386	0.9526
0.1479	3.0	2205	0.3214	0.8756	0.8212	0.8703	0.8450	0.7421	0.9524
0.1109	4.0	2940	0.4081	0.8841	0.8685	0.8279	0.8478	0.7548	0.9552
0.0616	5.0	3675	0.5643	0.8814	0.8554	0.8371	0.8462	0.7498	0.9527
0.0469	6.0	4410	0.6341	0.8844	0.8572	0.8441	0.8506	0.7565	0.9518
0.0312	7.0	5145	0.7977	0.8810	0.8913	0.7913	0.8383	0.7480	0.9506
0.0271	8.0	5880	0.7885	0.8850	0.8638	0.8367	0.8500	0.7570	0.9533
0.0228	9.0	6615	0.8030	0.8826	0.8591	0.8358	0.8473	0.7521	0.9524
0.0149	10.0	7350	0.8305	0.8834	0.8556	0.8432	0.8494	0.7543	0.9525