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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4022 |
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- Precision: 0.7421 |
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- Recall: 0.7951 |
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- F1: 0.7677 |
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- Accuracy: 0.8883 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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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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| 0.7548 | 1.0 | 680 | 0.4630 | 0.6857 | 0.7150 | 0.7000 | 0.8615 | |
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| 0.4124 | 2.0 | 1360 | 0.4143 | 0.7299 | 0.7698 | 0.7493 | 0.8786 | |
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| 0.2546 | 3.0 | 2040 | 0.4022 | 0.7421 | 0.7951 | 0.7677 | 0.8883 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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