Test training complete
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README.md
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---
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library_name: transformers
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base_model: dmis-lab/biobert-v1.1
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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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model-index:
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- name: b3r-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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# b3r-test
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This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6586
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- Precision: 0.5839
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- Recall: 0.6450
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- F1: 0.6129
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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: 0.00012839450868399685
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1685473261668876
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 1.0701 | 1.0 | 330 | 0.5494 | 0.5424 | 0.5540 | 0.5482 |
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| 0.4877 | 2.0 | 660 | 0.5052 | 0.5561 | 0.6069 | 0.5804 |
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| 0.3423 | 3.0 | 990 | 0.5166 | 0.5772 | 0.6301 | 0.6025 |
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| 0.2322 | 4.0 | 1320 | 0.5577 | 0.5766 | 0.6386 | 0.6060 |
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| 0.1555 | 5.0 | 1650 | 0.6107 | 0.5842 | 0.6423 | 0.6118 |
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| 0.1063 | 6.0 | 1980 | 0.6586 | 0.5839 | 0.6450 | 0.6129 |
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### Framework versions
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- Transformers 4.51.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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