phobert-human-tl-seg-seed-1337

This model is a fine-tuned version of vinai/phobert-base 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: 0.0001
train_batch_size: 64
eval_batch_size: 64
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
lr_scheduler_warmup_steps: 500
num_epochs: 50

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	346	0.5129	0.8256	0.5419	0.3574	0.3465
0.5863	2.0	692	0.4692	0.8383	0.6389	0.4354	0.4522
0.4602	3.0	1038	0.4660	0.8379	0.6454	0.4193	0.4386
0.4602	4.0	1384	0.4646	0.8387	0.6734	0.4254	0.4468
0.4568	5.0	1730	0.4581	0.8379	0.6411	0.4283	0.4489
0.45	6.0	2076	0.4585	0.8402	0.6567	0.4422	0.4615
0.45	7.0	2422	0.4631	0.8372	0.6626	0.4118	0.4318
0.4516	8.0	2768	0.4521	0.8413	0.6343	0.4509	0.4730
0.4475	9.0	3114	0.4538	0.8387	0.6594	0.4217	0.4441
0.4475	10.0	3460	0.4563	0.8439	0.6538	0.4632	0.4790
0.4509	11.0	3806	0.4531	0.8383	0.6474	0.4233	0.4484
0.4438	12.0	4152	0.4485	0.8432	0.6562	0.4696	0.4951
0.4438	13.0	4498	0.4503	0.8387	0.6479	0.4342	0.4618
0.4504	14.0	4844	0.4528	0.8391	0.6419	0.4251	0.4486
0.4423	15.0	5190	0.4528	0.8387	0.6390	0.4217	0.4450
0.4495	16.0	5536	0.4669	0.8372	0.6662	0.4110	0.4317
0.4495	17.0	5882	0.4475	0.8421	0.6441	0.4451	0.4700