metadata

license: mit
base_model: xlm-roberta-large
tags:
  - generated_from_trainer
datasets:
  - shipping_label_ner
model-index:
  - name: ner_bert_model
    results: []

ner_bert_model

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

eval_loss: 0.1076
eval_precision: 0.9091
eval_recall: 0.9524
eval_f1: 0.9302
eval_accuracy: 0.9691
eval_runtime: 0.325
eval_samples_per_second: 15.384
eval_steps_per_second: 9.23
epoch: 13.0
step: 130

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: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2