insights

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: 0.7686
• Accuracy: 0.8257

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	63	0.8631	0.7523
No log	2.0	126	0.7686	0.8257
No log	3.0	189	1.2180	0.7431
No log	4.0	252	1.1273	0.7982
No log	5.0	315	1.2937	0.7706
No log	6.0	378	1.3242	0.7890
No log	7.0	441	1.3387	0.7982
0.0916	8.0	504	1.2943	0.7706
0.0916	9.0	567	1.3299	0.7982
0.0916	10.0	630	1.3237	0.7982

Framework versions

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