2.18 kB
| --- | |
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - wikiann | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: mbert-finetuned-azerbaijani-ner | |
| results: | |
| - task: | |
| name: Token Classification | |
| type: token-classification | |
| dataset: | |
| name: wikiann | |
| type: wikiann | |
| args: az | |
| metrics: | |
| - name: Precision | |
| type: precision | |
| value: 0.8898541731306236 | |
| - name: Recall | |
| type: recall | |
| value: 0.915416533673795 | |
| - name: F1 | |
| type: f1 | |
| value: 0.9024543738200126 | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.966948310139165 | |
| --- | |
| <!-- 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. --> | |
| # mbert-finetuned-azerbaijani-ner | |
| This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1385 | |
| - Precision: 0.8899 | |
| - Recall: 0.9154 | |
| - F1: 0.9025 | |
| - 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: 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 | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.2928 | 1.0 | 625 | 0.1415 | 0.8584 | 0.8918 | 0.8748 | 0.9595 | | |
| | 0.1254 | 2.0 | 1250 | 0.1335 | 0.8875 | 0.9119 | 0.8996 | 0.9637 | | |
| | 0.077 | 3.0 | 1875 | 0.1385 | 0.8899 | 0.9154 | 0.9025 | 0.9669 | | |
| ### Framework versions | |
| - Transformers 4.16.2 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 1.18.3 | |
| - Tokenizers 0.11.6 | |