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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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- f1 |
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model-index: |
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- name: test |
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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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# test |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6886 |
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- Accuracy: 0.8143 |
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- F1: [0.92816572 0.56028369 0.1 0.2633452 ] |
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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: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------------------:| |
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| No log | 1.0 | 37 | 0.4891 | 0.8235 | [0.91702786 0.33333333 0. 0.10837438] | |
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| No log | 2.0 | 74 | 0.4762 | 0.8321 | [0.93139159 0.48466258 0. 0.22857143] | |
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| No log | 3.0 | 111 | 0.5084 | 0.8208 | [0.92995725 0.44887781 0. 0.19266055] | |
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| No log | 4.0 | 148 | 0.5519 | 0.8105 | [0.92421691 0.44444444 0.06557377 0.30769231] | |
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| No log | 5.0 | 185 | 0.5805 | 0.8294 | [0.93531353 0.52336449 0.09345794 0.27131783] | |
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| No log | 6.0 | 222 | 0.6778 | 0.7955 | [0.91344509 0.55305466 0.15463918 0.29166667] | |
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| No log | 7.0 | 259 | 0.6407 | 0.8213 | [0.93298292 0.51383399 0.10191083 0.2519084 ] | |
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| No log | 8.0 | 296 | 0.6639 | 0.8272 | [0.9326288 0.55052265 0.18181818 0.26271186] | |
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| No log | 9.0 | 333 | 0.6863 | 0.8192 | [0.93071286 0.55830389 0.11042945 0.2761194 ] | |
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| No log | 10.0 | 370 | 0.6886 | 0.8143 | [0.92816572 0.56028369 0.1 0.2633452 ] | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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