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--- |
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library_name: transformers |
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base_model: raulgdp/xml-roberta-large-finetuned-ner |
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tags: |
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- generated_from_trainer |
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datasets: |
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- biobert_json |
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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: NER-finetuning-XML-RoBERTa-BIOBERT |
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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: biobert_json |
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type: biobert_json |
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config: Biobert_json |
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split: validation |
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args: Biobert_json |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.937247539398077 |
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- name: Recall |
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type: recall |
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value: 0.964689348246179 |
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- name: F1 |
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type: f1 |
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value: 0.9507704738269752 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9773235561218265 |
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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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# NER-finetuning-XML-RoBERTa-BIOBERT |
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This model is a fine-tuned version of [raulgdp/xml-roberta-large-finetuned-ner](https://huggingface.co/raulgdp/xml-roberta-large-finetuned-ner) on the biobert_json dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1065 |
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- Precision: 0.9372 |
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- Recall: 0.9647 |
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- F1: 0.9508 |
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- Accuracy: 0.9773 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 5 |
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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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| 0.1305 | 1.0 | 2447 | 0.1005 | 0.9298 | 0.9680 | 0.9485 | 0.9747 | |
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| 0.0874 | 2.0 | 4894 | 0.0981 | 0.9406 | 0.9711 | 0.9556 | 0.9781 | |
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| 0.0782 | 3.0 | 7341 | 0.1023 | 0.9245 | 0.9577 | 0.9408 | 0.9747 | |
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| 0.0807 | 4.0 | 9788 | 0.1042 | 0.9316 | 0.9567 | 0.9440 | 0.9753 | |
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| 0.0437 | 5.0 | 12235 | 0.1065 | 0.9372 | 0.9647 | 0.9508 | 0.9773 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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