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--- |
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license: apache-2.0 |
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tags: |
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- token-classification |
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- generated_from_trainer |
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model-index: |
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- name: bert-base-cased-finetuned-WikiNeural |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-cased-finetuned-WikiNeural |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0881 |
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- Loc: {'precision': 0.9282034236330398, 'recall': 0.9378673383711167, 'f1': 0.9330103575008353, 'number': 5955} |
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- Misc: {'precision': 0.8336608897623727, 'recall': 0.9219521833629718, 'f1': 0.8755864139613436, 'number': 5061} |
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- Org: {'precision': 0.9351851851851852, 'recall': 0.9370832125253696, 'f1': 0.9361332367849385, 'number': 3449} |
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- Per: {'precision': 0.9728037566034045, 'recall': 0.9543186180422265, 'f1': 0.9634725317314214, 'number': 5210} |
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- Overall Precision: 0.9145 |
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- Overall Recall: 0.9380 |
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- Overall F1: 0.9261 |
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- Overall Accuracy: 0.9912 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Loc | Misc | Org | Per | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.1 | 1.0 | 5795 | 0.0943 | {'precision': 0.9075480846937126, 'recall': 0.9429051217464316, 'f1': 0.9248888156811068, 'number': 5955} | {'precision': 0.8320190720704199, 'recall': 0.8964631495751828, 'f1': 0.8630397565151225, 'number': 5061} | {'precision': 0.9151428571428571, 'recall': 0.9286749782545666, 'f1': 0.9218592603252267, 'number': 3449} | {'precision': 0.9683036587751908, 'recall': 0.9499040307101727, 'f1': 0.9590155992636372, 'number': 5210} | 0.9039 | 0.9303 | 0.9169 | 0.9901 | |
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| 0.0578 | 2.0 | 11590 | 0.0881 | {'precision': 0.9282034236330398, 'recall': 0.9378673383711167, 'f1': 0.9330103575008353, 'number': 5955} | {'precision': 0.8336608897623727, 'recall': 0.9219521833629718, 'f1': 0.8755864139613436, 'number': 5061} | {'precision': 0.9351851851851852, 'recall': 0.9370832125253696, 'f1': 0.9361332367849385, 'number': 3449} | {'precision': 0.9728037566034045, 'recall': 0.9543186180422265, 'f1': 0.9634725317314214, 'number': 5210} | 0.9145 | 0.9380 | 0.9261 | 0.9912 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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