glot500_model_en_ewt

This model is a fine-tuned version of cis-lmu/glot500-base on the universal_dependencies dataset. It achieves the following results on the evaluation set:

• Loss: 0.2101
• Precision: 0.9401
• Recall: 0.9421
• F1: 0.9411
• Accuracy: 0.9484

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.0519	1.0	625	0.2891	0.9291	0.9298	0.9295	0.9396
0.2366	2.0	1250	0.2101	0.9401	0.9421	0.9411	0.9484

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1
• Datasets 3.1.0
• Tokenizers 0.20.3