metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
base_model: bert-base-uncased
model-index:
- name: paraphrase_detector
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: glue
type: glue
config: mrpc
split: train
args: mrpc
metrics:
- type: accuracy
value: 0.8553921568627451
name: Accuracy
- type: f1
value: 0.8984509466437176
name: F1
paraphrase_detector
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6599
- Accuracy: 0.8554
- F1: 0.8985
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: 5e-05
- train_batch_size: 8
- 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 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.4968 | 0.8480 | 0.8901 |
| 0.3297 | 2.0 | 918 | 0.6599 | 0.8554 | 0.8985 |
| 0.1382 | 3.0 | 1377 | 0.6599 | 0.8554 | 0.8985 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1