lzh

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

• Loss: 0.3581
• Accuracy: 0.8850

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6577	1.0	125	0.5158	0.8432
0.4161	2.0	250	0.3891	0.8660
0.2767	3.0	375	0.3581	0.8850

Framework versions

• Transformers 4.44.1
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1