glot500_fintuned_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: 0.1532
• Precision: 0.9531
• Recall: 0.9549
• F1: 0.9540
• Accuracy: 0.9607

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
1.0263	1.0	784	0.2097	0.9385	0.9394	0.9389	0.9477
0.1409	2.0	1568	0.1532	0.9531	0.9549	0.9540	0.9607

Framework versions

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