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README.md
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---
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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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model-index:
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- name: ontochem_biobert_1e-5_10epochs_v2
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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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# ontochem_biobert_1e-5_10epochs_v2
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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: 0.0428
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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: 1e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 48 | 0.9247 |
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| No log | 2.0 | 96 | 0.4733 |
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| No log | 3.0 | 144 | 0.1217 |
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| No log | 4.0 | 192 | 0.0692 |
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| No log | 5.0 | 240 | 0.0546 |
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| No log | 6.0 | 288 | 0.0487 |
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| No log | 7.0 | 336 | 0.0461 |
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| No log | 8.0 | 384 | 0.0445 |
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| No log | 9.0 | 432 | 0.0447 |
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| No log | 10.0 | 480 | 0.0428 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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