metadata
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.9083848627256987
- name: F1
type: f1
value: 0.8767633750332712
bert-base-cased-finetuned-qqp
This model is a fine-tuned version of bert-base-cased on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.3752
- Accuracy: 0.9084
- F1: 0.8768
- Combined Score: 0.8926
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 | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.308 | 1.0 | 22741 | 0.2548 | 0.8925 | 0.8556 | 0.8740 |
| 0.201 | 2.0 | 45482 | 0.2881 | 0.9032 | 0.8698 | 0.8865 |
| 0.1416 | 3.0 | 68223 | 0.3752 | 0.9084 | 0.8768 | 0.8926 |
Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3