| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: microsoft/deberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: deberta-base-cased-finetuned-ner-final |
| | 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. --> |
| |
|
| | # deberta-base-cased-finetuned-ner-final |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4915 |
| | - Precision: 0.8451 |
| | - Recall: 0.8570 |
| | - F1: 0.8510 |
| | - Accuracy: 0.9669 |
| |
|
| | ## 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: 4.331046950257529e-05 |
| | - train_batch_size: 8 |
| | - 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 |
| | - lr_scheduler_warmup_ratio: 0.022489239711791377 |
| | - num_epochs: 4 |
| | - label_smoothing_factor: 0.0628867621783132 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.4906 | 1.0 | 4250 | 0.4915 | 0.8098 | 0.8309 | 0.8202 | 0.9619 | |
| | | 0.4703 | 2.0 | 8500 | 0.4831 | 0.8368 | 0.8407 | 0.8387 | 0.9649 | |
| | | 0.4488 | 3.0 | 12750 | 0.4850 | 0.8295 | 0.8531 | 0.8411 | 0.9651 | |
| | | 0.4245 | 4.0 | 17000 | 0.4915 | 0.8451 | 0.8570 | 0.8510 | 0.9669 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.1 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.21.1 |
| | |
