xlm-roberta-base-language-detection-silvanus

This model is a fine-tuned version of xlm-roberta-base on the common language and kiviki/SlovakSum datasets. It achieves the following results on the evaluation set:

• Loss: 0.0866
• Accuracy: 0.9868

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: 3e-05
• train_batch_size: 8
• eval_batch_size: 8
• 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
0.078	1.0	3188	0.1239	0.9784
0.0703	2.0	6376	0.1035	0.9830
0.0375	3.0	9564	0.0866	0.9868

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1