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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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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-question-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-question-ner |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2044 |
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- Precision: 0.7342 |
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- Recall: 0.7964 |
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- F1: 0.7640 |
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- Accuracy: 0.9338 |
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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: 9e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 6 |
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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 | 0.3311 | 100 | 1.1156 | 0.0 | 0.0 | 0.0 | 0.6528 | |
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| No log | 0.6623 | 200 | 0.6775 | 0.3169 | 0.4012 | 0.3541 | 0.7815 | |
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| No log | 0.9934 | 300 | 0.4010 | 0.5 | 0.6310 | 0.5579 | 0.8771 | |
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| No log | 1.3245 | 400 | 0.2844 | 0.6344 | 0.6996 | 0.6654 | 0.9046 | |
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| 0.7464 | 1.6556 | 500 | 0.2394 | 0.6404 | 0.7036 | 0.6705 | 0.9163 | |
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| 0.7464 | 1.9868 | 600 | 0.2204 | 0.6774 | 0.7661 | 0.7190 | 0.9241 | |
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| 0.7464 | 2.3179 | 700 | 0.2080 | 0.7143 | 0.7460 | 0.7298 | 0.9288 | |
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| 0.7464 | 2.6490 | 800 | 0.2044 | 0.7342 | 0.7964 | 0.7640 | 0.9338 | |
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| 0.7464 | 2.9801 | 900 | 0.2055 | 0.7227 | 0.7883 | 0.7541 | 0.9346 | |
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| 0.2123 | 3.3113 | 1000 | 0.2030 | 0.7361 | 0.7762 | 0.7556 | 0.9353 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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