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--- |
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license: mit |
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base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: ddi_42 |
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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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# ddi_42 |
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This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2085 |
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- Accuracy: 0.9551 |
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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: 256 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 791 | 0.1986 | 0.9383 | |
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| 0.1723 | 2.0 | 1582 | 0.2700 | 0.9455 | |
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| 0.0772 | 3.0 | 2373 | 0.2085 | 0.9551 | |
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| 0.0516 | 4.0 | 3164 | 0.2970 | 0.9427 | |
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| 0.0516 | 5.0 | 3955 | 0.2620 | 0.9539 | |
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| 0.0341 | 6.0 | 4746 | 0.3973 | 0.9423 | |
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| 0.0203 | 7.0 | 5537 | 0.3637 | 0.9423 | |
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| 0.0146 | 8.0 | 6328 | 0.4154 | 0.9451 | |
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| 0.007 | 9.0 | 7119 | 0.4219 | 0.9463 | |
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| 0.007 | 10.0 | 7910 | 0.4098 | 0.9447 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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