metadata
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.9099395936298736
bert-base-cased-finetuned-qnli
This model is a fine-tuned version of bert-base-cased on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.3986
- Accuracy: 0.9099
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: 3.0
Training results
Training Loss | Epoch | Step | Accuracy | Validation Loss |
---|---|---|---|---|
0.337 | 1.0 | 6547 | 0.9013 | 0.2448 |
0.1971 | 2.0 | 13094 | 0.9143 | 0.2839 |
0.1175 | 3.0 | 19641 | 0.9099 | 0.3986 |
Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3