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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ner_bert_model

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/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