---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Yaxin/SemEval2016Task5Raw
metrics:
- accuracy
model-index:
- name: bert-large-uncased-semeval2016-restaurants
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: Yaxin/SemEval2016Task5Raw restaurants_english
      type: Yaxin/SemEval2016Task5Raw
      config: restaurants_english
      split: validation
      args: restaurants_english
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7796610169491526
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-large-uncased-semeval2016-restaurants

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the Yaxin/SemEval2016Task5Raw restaurants_english dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0702
- Accuracy: 0.7797

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0

### Training results



### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2