| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: distilbert-base-uncased-finetuned-fin_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. --> |
|
|
| # distilbert-base-uncased-finetuned-fin_ner |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0887 |
| - Precision: 0.8198 |
| - Recall: 0.8292 |
| - F1: 0.8245 |
| - Accuracy: 0.9804 |
| |
| ## 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 204 | 0.0877 | 0.6569 | 0.7734 | 0.7104 | 0.9709 | |
| | No log | 2.0 | 408 | 0.0683 | 0.7931 | 0.7931 | 0.7931 | 0.9784 | |
| | 0.1032 | 3.0 | 612 | 0.0657 | 0.8325 | 0.8079 | 0.82 | 0.9796 | |
| | 0.1032 | 4.0 | 816 | 0.0696 | 0.7942 | 0.8112 | 0.8026 | 0.9783 | |
| | 0.0148 | 5.0 | 1020 | 0.0742 | 0.7987 | 0.8276 | 0.8129 | 0.9796 | |
| | 0.0148 | 6.0 | 1224 | 0.0788 | 0.7870 | 0.8374 | 0.8115 | 0.9787 | |
| | 0.0148 | 7.0 | 1428 | 0.0833 | 0.7933 | 0.8128 | 0.8029 | 0.9792 | |
| | 0.0066 | 8.0 | 1632 | 0.0833 | 0.8237 | 0.8440 | 0.8337 | 0.9806 | |
| | 0.0066 | 9.0 | 1836 | 0.0860 | 0.8185 | 0.8292 | 0.8238 | 0.9805 | |
| | 0.0042 | 10.0 | 2040 | 0.0887 | 0.8198 | 0.8292 | 0.8245 | 0.9804 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.53.1 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
| |
