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--- |
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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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model-index: |
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- name: prot_bert_classification_finetuned |
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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 |
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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: 0.5675 |
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- Accuracy: 0.7299 |
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- F1: 0.7377 |
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- Precision: 0.6995 |
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- Recall: 0.7803 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 3 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 5 |
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- num_epochs: 6 |
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- mixed_precision_training: Native AMP |
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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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| 0.4221 | 1.0 | 3332 | 0.6152 | 0.6615 | 0.6711 | 0.6367 | 0.7093 | |
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| 0.4133 | 2.0 | 6664 | 0.5840 | 0.6845 | 0.6718 | 0.6805 | 0.6634 | |
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| 0.4293 | 3.0 | 9996 | 0.5727 | 0.7116 | 0.7094 | 0.6961 | 0.7232 | |
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| 0.3098 | 4.0 | 13328 | 0.5636 | 0.7163 | 0.7220 | 0.6904 | 0.7566 | |
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| 0.3881 | 5.0 | 16660 | 0.5629 | 0.7265 | 0.7377 | 0.6918 | 0.7900 | |
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| 0.4943 | 6.0 | 19992 | 0.5675 | 0.7299 | 0.7377 | 0.6995 | 0.7803 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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