| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: bert-finetuned-ner-ime | |
| 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. --> | |
| # bert-finetuned-ner-ime | |
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 2.4592 | |
| - Precision: 0.6456 | |
| - Recall: 0.3813 | |
| - F1: 0.4794 | |
| - Accuracy: 0.6108 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - 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 | 221 | 2.6044 | 0.6263 | 0.3774 | 0.4710 | 0.6081 | | |
| | No log | 2.0 | 442 | 2.5040 | 0.6286 | 0.3848 | 0.4774 | 0.6100 | | |
| | 2.7612 | 3.0 | 663 | 2.4592 | 0.6456 | 0.3813 | 0.4794 | 0.6108 | | |
| ### Framework versions | |
| - Transformers 4.28.0 | |
| - Pytorch 2.0.1 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.11.0 | |