Complete
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README.md
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---
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license: mit
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base_model: microsoft/biogpt
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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: BioGPT_NCBI
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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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# BioGPT_NCBI
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This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1730
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- Precision: 0.4537
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- Recall: 0.5406
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- F1: 0.4933
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- Accuracy: 0.9493
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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: 4
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- eval_batch_size: 4
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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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| 0.2343 | 1.0 | 1358 | 0.1908 | 0.3555 | 0.4292 | 0.3889 | 0.9392 |
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| 0.1311 | 2.0 | 2716 | 0.1792 | 0.3994 | 0.5563 | 0.4650 | 0.9429 |
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| 0.081 | 3.0 | 4074 | 0.1730 | 0.4537 | 0.5406 | 0.4933 | 0.9493 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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