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--- |
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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: distilbert-base-uncased-finetuned-ner-harem |
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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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# distilbert-base-uncased-finetuned-ner-harem |
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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: 0.2626 |
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- Precision: 0.5556 |
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- Recall: 0.5565 |
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- F1: 0.5560 |
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- Accuracy: 0.9336 |
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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: 100 |
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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 | 282 | 0.3748 | 0.4065 | 0.2749 | 0.3280 | 0.9053 | |
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| 0.403 | 2.0 | 564 | 0.2924 | 0.5558 | 0.4705 | 0.5096 | 0.9266 | |
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| 0.403 | 3.0 | 846 | 0.2863 | 0.6589 | 0.5278 | 0.5861 | 0.9347 | |
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| 0.1961 | 4.0 | 1128 | 0.2626 | 0.5556 | 0.5565 | 0.5560 | 0.9336 | |
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| 0.1961 | 5.0 | 1410 | 0.2710 | 0.6279 | 0.5919 | 0.6094 | 0.9403 | |
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| 0.1074 | 6.0 | 1692 | 0.3046 | 0.6699 | 0.5818 | 0.6227 | 0.9408 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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