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README.md
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---
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license: cc0-1.0
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base_model: bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12
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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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- f1
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- accuracy
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model-index:
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- name: BlueBERT_BioNLP13CG_NER
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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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# BlueBERT_BioNLP13CG_NER
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This model is a fine-tuned version of [bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12](https://huggingface.co/bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2929
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- Precision: 0.9311
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- Recall: 0.9373
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- F1: 0.9342
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- Accuracy: 0.9309
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.99 | 95 | 0.4398 | 0.8891 | 0.8989 | 0.8940 | 0.8876 |
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| No log | 2.0 | 191 | 0.3148 | 0.9259 | 0.9325 | 0.9292 | 0.9252 |
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| No log | 2.98 | 285 | 0.2929 | 0.9311 | 0.9373 | 0.9342 | 0.9309 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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