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--- |
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language: |
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- en |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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- medical |
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datasets: |
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- opentargets/clinical_trial_reason_to_stop |
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metrics: |
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- accuracy |
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widget: |
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- text: Study stopped due to problems to recruit patients |
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example_title: Enrollment issues |
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- text: Efficacy endpoint unmet |
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example_title: Negative reasons |
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- text: Study stopped due to unexpected adverse effects |
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example_title: Safety |
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- text: Study paused due to the pandemic |
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example_title: COVID-19 |
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base_model: bert-base-uncased |
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model-index: |
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- name: stop_reasons_classificator_multilabel |
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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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# Clinical trial stop reasons |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the task of classification of why a clinical trial has stopped early. |
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The dataset containing 3,747 manually curated reasons used for fine-tuning is available in the [Hub](https://huggingface.co/datasets/opentargets/clinical_trial_reason_to_stop). |
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More details on the model training are available in the GitHub project ([link](https://github.com/opentargets/stopReasons)) and in the associated publication (DOI: 10.1038/s41588-024-01854-z). |
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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: 32 |
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- eval_batch_size: 32 |
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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: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:| |
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| No log | 1.0 | 106 | 0.1824 | 0.9475 | |
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| No log | 2.0 | 212 | 0.1339 | 0.9630 | |
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| No log | 3.0 | 318 | 0.1109 | 0.9689 | |
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| No log | 4.0 | 424 | 0.0988 | 0.9741 | |
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| 0.1439 | 5.0 | 530 | 0.0943 | 0.9743 | |
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| 0.1439 | 6.0 | 636 | 0.0891 | 0.9763 | |
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| 0.1439 | 7.0 | 742 | 0.0899 | 0.9760 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
