UNER_subword_tk_en_lora_alpha_512_drop_0.2_rank_256_seed_42_lr_3e-5

This model is a fine-tuned version of xlm-roberta-base on the universalner/universal_ner en_ewt dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.6475
• eval_precision: 0.0045
• eval_recall: 0.0269
• eval_f1: 0.0077
• eval_accuracy: 0.3062
• eval_runtime: 1.3804
• eval_samples_per_second: 1449.554
• eval_steps_per_second: 45.638
• 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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20.0

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1