| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: distilbert-base-uncased-finetuned-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-ner | |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1079 | |
| - Precision: 0.8408 | |
| - Recall: 0.8686 | |
| - F1: 0.8545 | |
| - Accuracy: 0.9638 | |
| ## 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: 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 | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | No log | 1.0 | 453 | 0.1322 | 0.7759 | 0.8370 | 0.8053 | 0.9498 | | |
| | 0.246 | 2.0 | 906 | 0.1115 | 0.8284 | 0.8616 | 0.8446 | 0.9611 | | |
| | 0.1012 | 3.0 | 1359 | 0.1079 | 0.8408 | 0.8686 | 0.8545 | 0.9638 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |