metadata
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- OpenTable
metrics:
- accuracy
model-index:
- name: roberta-base.CEBaB_confounding.uniform.sa.5-class.seed_43
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: OpenTable OPENTABLE
type: OpenTable
args: opentable
metrics:
- name: Accuracy
type: accuracy
value: 0.735803945008966
roberta-base.CEBaB_confounding.uniform.sa.5-class.seed_43
This model is a fine-tuned version of roberta-base on the OpenTable OPENTABLE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6596
- Accuracy: 0.7358
- Macro-f1: 0.7204
- Weighted-macro-f1: 0.7325
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