| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: BERT_token_classification_18_techs |
| 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_18_techs |
|
|
| 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: 0.0228 |
| - Precision: 0.8769 |
| - Recall: 0.9215 |
| - F1: 0.8987 |
| - Accuracy: 0.9927 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.6 | 1.0 | 1907 | 0.4260 | 0.3545 | 0.1303 | 0.1906 | 0.8856 | |
| | 0.4035 | 2.0 | 3814 | 0.2568 | 0.4196 | 0.2961 | 0.3472 | 0.9224 | |
| | 0.2808 | 3.0 | 5721 | 0.1464 | 0.5921 | 0.5058 | 0.5456 | 0.9568 | |
| | 0.1648 | 4.0 | 7628 | 0.0952 | 0.6679 | 0.6614 | 0.6646 | 0.9717 | |
| | 0.1138 | 5.0 | 9535 | 0.0708 | 0.7138 | 0.7422 | 0.7277 | 0.9781 | |
| | 0.0899 | 6.0 | 11442 | 0.0516 | 0.7779 | 0.7950 | 0.7863 | 0.9840 | |
| | 0.0609 | 7.0 | 13349 | 0.0357 | 0.8352 | 0.8496 | 0.8423 | 0.9888 | |
| | 0.0503 | 8.0 | 15256 | 0.0269 | 0.8677 | 0.9010 | 0.8841 | 0.9915 | |
| | 0.0376 | 9.0 | 17163 | 0.0248 | 0.8700 | 0.9155 | 0.8921 | 0.9920 | |
| | 0.0331 | 10.0 | 19070 | 0.0228 | 0.8769 | 0.9215 | 0.8987 | 0.9927 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.13.3 |
|
|
