CS505-Classifier-T4_predictLabel_a1_v8

This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0078

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.99	97	0.5015
No log	1.98	194	0.3145
No log	2.97	291	0.2217
No log	3.96	388	0.1995
No log	4.95	485	0.1427
0.4489	5.94	582	0.1056
0.4489	6.93	679	0.0765
0.4489	7.92	776	0.0530
0.4489	8.91	873	0.0605
0.4489	9.9	970	0.0387
0.1098	10.89	1067	0.0360
0.1098	11.88	1164	0.0179
0.1098	12.87	1261	0.0104
0.1098	13.86	1358	0.0135
0.1098	14.85	1455	0.0066
0.0301	15.84	1552	0.0137
0.0301	16.83	1649	0.0078

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2