nmp

This model is a fine-tuned version of bert-base-multilingual-uncased on the custom dataset. It achieves the following results on the evaluation set:

• Loss: 0.0803
• Accuracy: 0.9688

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	19	1.4407	0.3438
No log	2.0	38	0.6772	0.9375
No log	3.0	57	0.2852	0.9688
No log	4.0	76	0.0846	1.0
No log	5.0	95	0.0803	0.9688
No log	6.0	114	0.1039	0.9688
No log	7.0	133	0.1371	0.9688
No log	8.0	152	0.1239	0.9688
No log	9.0	171	0.1325	0.9688
No log	10.0	190	0.1312	0.9688

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2