my_awesome_wnut_model

This model is a fine-tuned version of distilbert-base-uncased on the shipping_label_ner dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0550
• eval_precision: 0.9286
• eval_recall: 0.9630
• eval_f1: 0.9455
• eval_accuracy: 0.9904
• eval_runtime: 0.046
• eval_samples_per_second: 108.697
• eval_steps_per_second: 21.739
• epoch: 55.0
• step: 110

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: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 100

Framework versions

• Transformers 4.40.0.dev0
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2