metadata
language:
- en
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-large-boolq
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE BOOLQ
type: glue
args: boolq
metrics:
- name: Accuracy
type: accuracy
value: 0.7189602446483181
bert-large-boolq
This model is a fine-tuned version of bert-large-cased on the GLUE BOOLQ dataset. It achieves the following results on the evaluation set:
- Loss: 1.4813
- Accuracy: 0.7190
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: 16
- eval_batch_size: 8
- seed: 42
- 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 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3