prot_bert_classification_finetuned_karolina_es_20e
This model is a fine-tuned version of nepp1d0/prot_bert-finetuned-smiles-bindingDB on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6763
- Accuracy: 0.92
- F1: 0.9583
- Precision: 1.0
- Recall: 0.92
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 2 | 0.7084 | 0.02 | 0.0392 | 1.0 | 0.02 |
No log | 2.0 | 4 | 0.7082 | 0.02 | 0.0392 | 1.0 | 0.02 |
No log | 3.0 | 6 | 0.7078 | 0.04 | 0.0769 | 1.0 | 0.04 |
No log | 4.0 | 8 | 0.7072 | 0.04 | 0.0769 | 1.0 | 0.04 |
No log | 5.0 | 10 | 0.7065 | 0.04 | 0.0769 | 1.0 | 0.04 |
No log | 6.0 | 12 | 0.7055 | 0.04 | 0.0769 | 1.0 | 0.04 |
No log | 7.0 | 14 | 0.7044 | 0.04 | 0.0769 | 1.0 | 0.04 |
No log | 8.0 | 16 | 0.7031 | 0.06 | 0.1132 | 1.0 | 0.06 |
No log | 9.0 | 18 | 0.7017 | 0.12 | 0.2143 | 1.0 | 0.12 |
No log | 10.0 | 20 | 0.6999 | 0.2 | 0.3333 | 1.0 | 0.2 |
No log | 11.0 | 22 | 0.6981 | 0.22 | 0.3607 | 1.0 | 0.22 |
No log | 12.0 | 24 | 0.6962 | 0.22 | 0.3607 | 1.0 | 0.22 |
No log | 13.0 | 26 | 0.6941 | 0.24 | 0.3871 | 1.0 | 0.24 |
No log | 14.0 | 28 | 0.6917 | 0.44 | 0.6111 | 1.0 | 0.44 |
No log | 15.0 | 30 | 0.6893 | 0.58 | 0.7342 | 1.0 | 0.58 |
No log | 16.0 | 32 | 0.6869 | 0.76 | 0.8636 | 1.0 | 0.76 |
No log | 17.0 | 34 | 0.6842 | 0.88 | 0.9362 | 1.0 | 0.88 |
No log | 18.0 | 36 | 0.6816 | 0.9 | 0.9474 | 1.0 | 0.9 |
No log | 19.0 | 38 | 0.6789 | 0.92 | 0.9583 | 1.0 | 0.92 |
No log | 20.0 | 40 | 0.6763 | 0.92 | 0.9583 | 1.0 | 0.92 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.11.0
- Datasets 2.6.1
- Tokenizers 0.13.1
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