intent_classfication

This model is a fine-tuned version of google-bert/bert-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: 2e-05
train_batch_size: 16
eval_batch_size: 16
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: 15

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.647	1.0	655	1.0548	0.8502
1.0688	2.0	1310	0.5307	0.8945
0.683	3.0	1965	0.3331	0.9255
0.3873	4.0	2620	0.2548	0.9396
0.326	5.0	3275	0.2134	0.9480
0.29	6.0	3930	0.1842	0.9538
0.2409	7.0	4585	0.1675	0.9553
0.2292	8.0	5240	0.1594	0.9576
0.2217	9.0	5895	0.1492	0.9595
0.2029	10.0	6550	0.1433	0.9595
0.2036	11.0	7205	0.1369	0.9614
0.1865	12.0	7860	0.1347	0.9614
0.1899	13.0	8515	0.1327	0.9622
0.182	14.0	9170	0.1315	0.9622
0.181	15.0	9825	0.1313	0.9622

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