xlm-roberta-large-finetuned-ner

This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 3.1818
• eval_precision: 0.0185
• eval_recall: 0.0749
• eval_f1: 0.0296
• eval_accuracy: 0.0005
• eval_runtime: 149.7208
• eval_samples_per_second: 72.475
• eval_steps_per_second: 18.12
• step: 0

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0