| --- |
| license: apache-2.0 |
| base_model: distilbert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: distilbert_system_B |
| results: [] |
| datasets: |
| - Babelscape/multinerd |
| language: |
| - en |
| --- |
| |
| <!-- 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_system_B |
|
|
| This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0293 |
| - Precision: 0.9456 |
| - Recall: 0.9531 |
| - F1: 0.9493 |
| - Accuracy: 0.9931 |
|
|
| ## 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: 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: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.0134 | 1.0 | 8205 | 0.0208 | 0.9466 | 0.9488 | 0.9477 | 0.9929 | |
| | 0.0067 | 2.0 | 16410 | 0.0237 | 0.9453 | 0.9528 | 0.9490 | 0.9931 | |
| | 0.0031 | 3.0 | 24615 | 0.0293 | 0.9456 | 0.9531 | 0.9493 | 0.9931 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
