xlm-roberta-large-finetuned-ner

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

• eval_loss: 0.2329
• eval_precision: 0.7110
• eval_recall: 0.6854
• eval_f1: 0.6980
• eval_accuracy: 0.9332
• eval_runtime: 162.3478
• eval_samples_per_second: 66.9
• eval_steps_per_second: 16.73
• epoch: 2.64
• step: 50198

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 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1