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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-finetuned-ner |
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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-finetuned-ner |
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1622 |
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- Precision: 0.7774 |
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- Recall: 0.7937 |
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- F1: 0.7854 |
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- Accuracy: 0.9707 |
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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: 8e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 131 | 0.1355 | 0.6880 | 0.7298 | 0.7083 | 0.9604 | |
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| No log | 2.0 | 262 | 0.1194 | 0.7564 | 0.7727 | 0.7645 | 0.9684 | |
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| No log | 3.0 | 393 | 0.1277 | 0.7731 | 0.7868 | 0.7799 | 0.9691 | |
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| 0.0433 | 4.0 | 524 | 0.1433 | 0.7553 | 0.7829 | 0.7688 | 0.9685 | |
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| 0.0433 | 5.0 | 655 | 0.1515 | 0.7734 | 0.7946 | 0.7839 | 0.9700 | |
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| 0.0433 | 6.0 | 786 | 0.1518 | 0.7819 | 0.8008 | 0.7912 | 0.9708 | |
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| 0.0433 | 7.0 | 917 | 0.1602 | 0.7752 | 0.7914 | 0.7832 | 0.9704 | |
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| 0.0094 | 8.0 | 1048 | 0.1622 | 0.7774 | 0.7937 | 0.7854 | 0.9707 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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