---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- OpenTable
metrics:
- accuracy
model-index:
- name: roberta-base.CEBaB_confounding.observational.absa.5-class.seed_43
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: OpenTable OPENTABLE-ABSA
      type: OpenTable
      args: opentable-absa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8857609139126887
---

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# roberta-base.CEBaB_confounding.observational.absa.5-class.seed_43

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the OpenTable OPENTABLE-ABSA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4706
- Accuracy: 0.8858
- Macro-f1: 0.8840
- Weighted-macro-f1: 0.8860

## 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: 32
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.5.2
- Tokenizers 0.12.1