| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - indian_names |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: my_awesome_wnut_model |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: indian_names |
| type: indian_names |
| config: indian_names |
| split: train |
| args: indian_names |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.7241379310344828 |
| - name: Recall |
| type: recall |
| value: 0.7170731707317073 |
| - name: F1 |
| type: f1 |
| value: 0.7205882352941175 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9920721492851299 |
| --- |
| |
| <!-- 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. --> |
|
|
| # my_awesome_wnut_model |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indian_names dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0278 |
| - Precision: 0.7241 |
| - Recall: 0.7171 |
| - F1: 0.7206 |
| - Accuracy: 0.9921 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 63 | 0.1197 | 0.0 | 0.0 | 0.0 | 0.9745 | |
| | No log | 2.0 | 126 | 0.0818 | 0.8438 | 0.0263 | 0.0511 | 0.9751 | |
| | No log | 3.0 | 189 | 0.0470 | 0.5270 | 0.4859 | 0.5056 | 0.9857 | |
| | No log | 4.0 | 252 | 0.0315 | 0.7042 | 0.6341 | 0.6674 | 0.9906 | |
| | No log | 5.0 | 315 | 0.0278 | 0.7241 | 0.7171 | 0.7206 | 0.9921 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.33.1 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
