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--- |
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license: mit |
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base_model: Tsubasaz/clinical-pubmed-bert-base-512 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: model |
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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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# model |
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This model is a fine-tuned version of [Tsubasaz/clinical-pubmed-bert-base-512](https://huggingface.co/Tsubasaz/clinical-pubmed-bert-base-512) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3511 |
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- Precision: 0.6103 |
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- Recall: 0.5640 |
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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: 3e-06 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| No log | 1.0 | 128 | 0.4393 | 0.0 | 0.0 | |
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| No log | 2.0 | 256 | 0.3958 | 0.5714 | 0.1706 | |
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| No log | 3.0 | 384 | 0.3785 | 0.5690 | 0.3128 | |
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| 0.4046 | 4.0 | 512 | 0.3676 | 0.5789 | 0.5213 | |
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| 0.4046 | 5.0 | 640 | 0.3606 | 0.6532 | 0.3839 | |
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| 0.4046 | 6.0 | 768 | 0.3597 | 0.6549 | 0.4408 | |
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| 0.4046 | 7.0 | 896 | 0.3584 | 0.6376 | 0.4502 | |
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| 0.3046 | 8.0 | 1024 | 0.3518 | 0.6310 | 0.5024 | |
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| 0.3046 | 9.0 | 1152 | 0.3511 | 0.6133 | 0.5261 | |
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| 0.3046 | 10.0 | 1280 | 0.3511 | 0.6103 | 0.5640 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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