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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: 0.9497881598534296 |
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- name: Recall |
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type: recall |
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value: 0.9714235521461615 |
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- name: F1 |
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type: f1 |
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value: 0.9604840343919173 |
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- name: Accuracy |
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type: accuracy |
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value: 0.981362755330252 |
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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: 0.0946 |
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- Precision: 0.9498 |
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- Recall: 0.9714 |
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- F1: 0.9605 |
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- Accuracy: 0.9814 |
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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: 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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| 0.1306 | 1.0 | 1224 | 0.1013 | 0.9299 | 0.9609 | 0.9451 | 0.9735 | |
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| 0.0996 | 2.0 | 2448 | 0.0932 | 0.9383 | 0.9656 | 0.9517 | 0.9777 | |
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| 0.0608 | 3.0 | 3672 | 0.0865 | 0.9493 | 0.9720 | 0.9605 | 0.9813 | |
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| 0.0445 | 4.0 | 4896 | 0.0927 | 0.9531 | 0.9729 | 0.9629 | 0.9819 | |
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| 0.0327 | 5.0 | 6120 | 0.0946 | 0.9498 | 0.9714 | 0.9605 | 0.9814 | |
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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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