| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: output |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # output |
| |
|
| | This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7643 |
| | - Accuracy: 0.8686 |
| | - Precision: 0.8681 |
| | - Recall: 0.8686 |
| | - F1: 0.8673 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 7 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.2969 | 1.0 | 505 | 0.6707 | 0.8376 | 0.8375 | 0.8376 | 0.8320 | |
| | | 0.2567 | 2.0 | 1010 | 0.6184 | 0.8572 | 0.8516 | 0.8572 | 0.8519 | |
| | | 0.1496 | 3.0 | 1515 | 0.6471 | 0.8693 | 0.8637 | 0.8693 | 0.8651 | |
| | | 0.0826 | 4.0 | 2020 | 0.6897 | 0.8641 | 0.8600 | 0.8641 | 0.8604 | |
| | | 0.0467 | 5.0 | 2525 | 0.7378 | 0.8676 | 0.8671 | 0.8676 | 0.8663 | |
| | | 0.0229 | 6.0 | 3030 | 0.7521 | 0.8678 | 0.8670 | 0.8678 | 0.8666 | |
| | | 0.01 | 7.0 | 3535 | 0.7643 | 0.8686 | 0.8681 | 0.8686 | 0.8673 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.2 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.15.0 |
| |
|
