| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model_index: |
| | - name: finetuned-bert-mrpc |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: glue |
| | type: glue |
| | args: mrpc |
| | metric: |
| | name: F1 |
| | type: f1 |
| | value: 0.8791946308724832 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # finetuned-bert-mrpc |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4917 |
| | - Accuracy: 0.8235 |
| | - F1: 0.8792 |
| |
|
| | ## 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: 16 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | 0.5382 | 1.0 | 230 | 0.4008 | 0.8456 | 0.8893 | |
| | | 0.3208 | 2.0 | 460 | 0.4182 | 0.8309 | 0.8844 | |
| | | 0.1587 | 3.0 | 690 | 0.4917 | 0.8235 | 0.8792 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.9.0.dev0 |
| | - Pytorch 1.8.1+cu111 |
| | - Datasets 1.8.1.dev0 |
| | - Tokenizers 0.10.1 |
| |
|
