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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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base_model: nepp1d0/prot_bert-finetuned-smiles-bindingDB |
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model-index: |
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- name: prot_bert_classification_finetuned_karolina_es_10e |
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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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# prot_bert_classification_finetuned_karolina_es_10e |
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This model is a fine-tuned version of [nepp1d0/prot_bert-finetuned-smiles-bindingDB](https://huggingface.co/nepp1d0/prot_bert-finetuned-smiles-bindingDB) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6840 |
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- Accuracy: 0.88 |
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- F1: 0.9362 |
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- Precision: 1.0 |
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- Recall: 0.88 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 3 |
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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: 100 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 4 | 0.7082 | 0.02 | 0.0392 | 1.0 | 0.02 | |
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| No log | 2.0 | 8 | 0.7073 | 0.04 | 0.0769 | 1.0 | 0.04 | |
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| No log | 3.0 | 12 | 0.7060 | 0.04 | 0.0769 | 1.0 | 0.04 | |
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| No log | 4.0 | 16 | 0.7047 | 0.04 | 0.0769 | 1.0 | 0.04 | |
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| No log | 5.0 | 20 | 0.7034 | 0.08 | 0.1481 | 1.0 | 0.08 | |
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| No log | 6.0 | 24 | 0.7008 | 0.22 | 0.3607 | 1.0 | 0.22 | |
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| No log | 7.0 | 28 | 0.6976 | 0.22 | 0.3607 | 1.0 | 0.22 | |
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| No log | 8.0 | 32 | 0.6933 | 0.3 | 0.4615 | 1.0 | 0.3 | |
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| No log | 9.0 | 36 | 0.6893 | 0.6 | 0.7500 | 1.0 | 0.6 | |
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| No log | 10.0 | 40 | 0.6840 | 0.88 | 0.9362 | 1.0 | 0.88 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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