| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: token_classification_NER |
| 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. --> |
|
|
| # token_classification_NER |
|
|
| This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2930 |
| - Precision: 0.5538 |
| - Recall: 0.3577 |
| - F1: 0.4347 |
| - Accuracy: 0.9460 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 213 | 0.2876 | 0.5724 | 0.2419 | 0.3401 | 0.9382 | |
| | No log | 2.0 | 426 | 0.2626 | 0.5434 | 0.3133 | 0.3974 | 0.9431 | |
| | 0.1852 | 3.0 | 639 | 0.2846 | 0.5399 | 0.3262 | 0.4067 | 0.9446 | |
| | 0.1852 | 4.0 | 852 | 0.2875 | 0.5536 | 0.3494 | 0.4284 | 0.9458 | |
| | 0.0547 | 5.0 | 1065 | 0.2930 | 0.5538 | 0.3577 | 0.4347 | 0.9460 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.53.3 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
|
|
