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End of training
Browse files- README.md +68 -0
- model.safetensors +1 -1
README.md
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---
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license: mit
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base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
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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: PubMedBERT_CRAFT_NER_new
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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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# PubMedBERT_CRAFT_NER_new
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1034
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- Precision: 0.9811
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- Recall: 0.9782
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- F1: 0.9797
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- Accuracy: 0.9751
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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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- 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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| 0.2176 | 1.0 | 695 | 0.1101 | 0.9780 | 0.9739 | 0.9759 | 0.9708 |
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| 0.0555 | 2.0 | 1390 | 0.1019 | 0.9800 | 0.9770 | 0.9785 | 0.9739 |
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| 0.0283 | 3.0 | 2085 | 0.1034 | 0.9811 | 0.9782 | 0.9797 | 0.9751 |
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 435629924
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version https://git-lfs.github.com/spec/v1
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size 435629924
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