metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: pizza-ner2
results: []
pipeline_tag: token-classification
widget:
- text: Can I get a Veggie Supreme Pizza with Pineapple toppings?
example_title: Pizza
- text: Can I get a cheese pizza with a coke?
example_title: Drink
- text: >-
Can I get a Margherita Pizza, three Chicken Pizza with ham and bacon and
five bottles of coke?
example_title: Complex Order
- text: What all non-veg pizza options you have ?
example_title: Category Type
Pizza NER
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0172
- F1: 0.9879
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0382 | 1.0 | 10468 | 0.0172 | 0.9879 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1