| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: BERT_token_classification_14PTC_basic_fixed |
| 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. --> |
|
|
| # BERT_token_classification_14PTC_basic_fixed |
| |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2901 |
| - Precision: 0.0593 |
| - Recall: 0.0755 |
| - F1: 0.0664 |
| - Accuracy: 0.7149 |
| |
| ## 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: 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 1.1822 | 1.0 | 664 | 0.9721 | 0.1063 | 0.0329 | 0.0502 | 0.7774 | |
| | 0.9937 | 2.0 | 1328 | 0.9852 | 0.0607 | 0.0622 | 0.0614 | 0.7508 | |
| | 0.8517 | 3.0 | 1992 | 0.9996 | 0.0572 | 0.0577 | 0.0574 | 0.7376 | |
| | 0.5704 | 4.0 | 2656 | 1.0643 | 0.0545 | 0.0657 | 0.0596 | 0.7296 | |
| | 0.514 | 5.0 | 3320 | 1.1014 | 0.0555 | 0.0648 | 0.0598 | 0.7318 | |
| | 0.4757 | 6.0 | 3984 | 1.1413 | 0.0565 | 0.0568 | 0.0567 | 0.7356 | |
| | 0.3538 | 7.0 | 4648 | 1.2095 | 0.0598 | 0.0764 | 0.0671 | 0.7171 | |
| | 0.3326 | 8.0 | 5312 | 1.2463 | 0.0551 | 0.0728 | 0.0627 | 0.7081 | |
| | 0.3158 | 9.0 | 5976 | 1.2557 | 0.0636 | 0.0764 | 0.0694 | 0.7258 | |
| | 0.2676 | 10.0 | 6640 | 1.2901 | 0.0593 | 0.0755 | 0.0664 | 0.7149 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.30.2 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.13.3 |
| |
