| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: glue_sst_classifier |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: glue |
| | type: glue |
| | args: sst2 |
| | metrics: |
| | - name: F1 |
| | type: f1 |
| | value: 0.9033707865168539 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9013761467889908 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # glue_sst_classifier |
| |
|
| | 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: 0.2359 |
| | - F1: 0.9034 |
| | - Accuracy: 0.9014 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 128 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 1.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
| | | 0.3653 | 0.19 | 100 | 0.3213 | 0.8717 | 0.8727 | |
| | | 0.291 | 0.38 | 200 | 0.2662 | 0.8936 | 0.8911 | |
| | | 0.2239 | 0.57 | 300 | 0.2417 | 0.9081 | 0.9060 | |
| | | 0.2306 | 0.76 | 400 | 0.2359 | 0.9105 | 0.9094 | |
| | | 0.2185 | 0.95 | 500 | 0.2371 | 0.9011 | 0.8991 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.18.0 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.12.1 |
| | |
