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--- |
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license: apache-2.0 |
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base_model: dslim/distilbert-NER |
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tags: |
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- generated_from_trainer |
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datasets: |
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- conll2012_ontonotesv5 |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert-NER-finetuned |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: conll2012_ontonotesv5 |
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type: conll2012_ontonotesv5 |
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config: english_v4 |
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split: validation |
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args: english_v4 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.867816091954023 |
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- name: F1 |
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type: f1 |
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value: 0.4862665310274669 |
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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-NER-finetuned |
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This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the conll2012_ontonotesv5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5043 |
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- Accuracy: 0.8678 |
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- F1: 0.4863 |
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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: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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 | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.9019 | 1.0 | 61 | 0.6286 | 0.8406 | 0.4223 | |
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| 0.5594 | 2.0 | 122 | 0.5302 | 0.8605 | 0.4567 | |
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| 0.4537 | 3.0 | 183 | 0.5043 | 0.8678 | 0.4863 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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