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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: bert-base-uncased |
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model-index: |
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- name: clinical_trial_stop_reasons_custom |
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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_custom |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1448 |
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- Accuracy Thresh: 0.9570 |
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- F1 Micro: 0.5300 |
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- F1 Macro: 0.1254 |
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- Confusion Matrix: [[5940 15] |
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[ 270 150]] |
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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: 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 | F1 Micro | F1 Macro | Confusion Matrix | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:--------:|:--------:|:--------------------------:| |
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| No log | 1.0 | 106 | 0.2812 | 0.8328 | 0.0 | 0.0 | [[5955 0] |
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[ 420 0]] | |
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| No log | 2.0 | 212 | 0.2189 | 0.9382 | 0.0 | 0.0 | [[5955 0] |
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[ 420 0]] | |
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| No log | 3.0 | 318 | 0.1840 | 0.9489 | 0.0 | 0.0 | [[5955 0] |
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[ 420 0]] | |
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| No log | 4.0 | 424 | 0.1638 | 0.9485 | 0.4940 | 0.0989 | [[5943 12] |
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[ 288 132]] | |
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| 0.239 | 5.0 | 530 | 0.1526 | 0.9533 | 0.5060 | 0.1018 | [[5943 12] |
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[ 277 143]] | |
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| 0.239 | 6.0 | 636 | 0.1467 | 0.9564 | 0.5077 | 0.1020 | [[5938 17] |
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[ 275 145]] | |
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| 0.239 | 7.0 | 742 | 0.1448 | 0.9570 | 0.5300 | 0.1254 | [[5940 15] |
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[ 270 150]] | |
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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 |
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