| | --- |
| | license: apache-2.0 |
| | tags: |
| | - text-classification |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: NLP_sequence_clasiffication |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: glue |
| | type: glue |
| | config: mrpc |
| | split: validation |
| | args: mrpc |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.8504901960784313 |
| | - name: F1 |
| | type: f1 |
| | value: 0.8872458410351203 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # NLP_sequence_clasiffication |
| |
|
| | This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue and the mrpc datasets. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5325 |
| | - Accuracy: 0.8505 |
| | - F1: 0.8872 |
| |
|
| | ## 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 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | 0.5129 | 1.09 | 500 | 0.7246 | 0.8113 | 0.8679 | |
| | | 0.3526 | 2.18 | 1000 | 0.5325 | 0.8505 | 0.8872 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.2 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.13.3 |
| |
|
