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--- |
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license: apache-2.0 |
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base_model: Dr-BERT/DrBERT-7GB |
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tags: |
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- generated_from_trainer |
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datasets: |
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- quaero |
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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: drbert-7gb-finedtuned-ner |
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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: quaero |
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type: quaero |
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config: medline |
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split: validation |
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args: medline |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.5055292259083728 |
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- name: Recall |
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type: recall |
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value: 0.5696484201157098 |
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- name: F1 |
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type: f1 |
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value: 0.5356769198577107 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8004338394793926 |
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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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# drbert-7gb-finedtuned-ner |
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This model is a fine-tuned version of [Dr-BERT/DrBERT-7GB](https://huggingface.co/Dr-BERT/DrBERT-7GB) on the quaero dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2330 |
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- Precision: 0.5055 |
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- Recall: 0.5696 |
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- F1: 0.5357 |
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- Accuracy: 0.8004 |
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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: 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: 10 |
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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 | 105 | 0.7430 | 0.4129 | 0.4775 | 0.4428 | 0.7671 | |
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| No log | 2.0 | 210 | 0.6968 | 0.4888 | 0.5042 | 0.4964 | 0.7888 | |
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| No log | 3.0 | 315 | 0.8218 | 0.5059 | 0.5323 | 0.5188 | 0.7952 | |
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| No log | 4.0 | 420 | 0.9307 | 0.4869 | 0.5563 | 0.5193 | 0.7913 | |
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| 0.4134 | 5.0 | 525 | 0.9970 | 0.4688 | 0.5581 | 0.5095 | 0.7870 | |
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| 0.4134 | 6.0 | 630 | 1.0503 | 0.4992 | 0.5541 | 0.5252 | 0.7930 | |
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| 0.4134 | 7.0 | 735 | 1.1364 | 0.5034 | 0.5607 | 0.5305 | 0.7994 | |
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| 0.4134 | 8.0 | 840 | 1.1994 | 0.4865 | 0.5701 | 0.5250 | 0.7937 | |
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| 0.4134 | 9.0 | 945 | 1.2287 | 0.4948 | 0.5683 | 0.5290 | 0.7982 | |
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| 0.028 | 10.0 | 1050 | 1.2330 | 0.5055 | 0.5696 | 0.5357 | 0.8004 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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