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prot_bert_classification_finetuned_karolina_es_20e

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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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_karolina_es_20e
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+ results: []
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+ ---
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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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+
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+ # prot_bert_classification_finetuned_karolina_es_20e
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+
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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: 0.6763
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+ - Accuracy: 0.92
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+ - F1: 0.9583
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+ - Precision: 1.0
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+ - Recall: 0.92
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 64
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+ - eval_batch_size: 64
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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: 20
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+
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+ ### Training results
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+
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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 | 2 | 0.7084 | 0.02 | 0.0392 | 1.0 | 0.02 |
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+ | No log | 2.0 | 4 | 0.7082 | 0.02 | 0.0392 | 1.0 | 0.02 |
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+ | No log | 3.0 | 6 | 0.7078 | 0.04 | 0.0769 | 1.0 | 0.04 |
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+ | No log | 4.0 | 8 | 0.7072 | 0.04 | 0.0769 | 1.0 | 0.04 |
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+ | No log | 5.0 | 10 | 0.7065 | 0.04 | 0.0769 | 1.0 | 0.04 |
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+ | No log | 6.0 | 12 | 0.7055 | 0.04 | 0.0769 | 1.0 | 0.04 |
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+ | No log | 7.0 | 14 | 0.7044 | 0.04 | 0.0769 | 1.0 | 0.04 |
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+ | No log | 8.0 | 16 | 0.7031 | 0.06 | 0.1132 | 1.0 | 0.06 |
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+ | No log | 9.0 | 18 | 0.7017 | 0.12 | 0.2143 | 1.0 | 0.12 |
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+ | No log | 10.0 | 20 | 0.6999 | 0.2 | 0.3333 | 1.0 | 0.2 |
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+ | No log | 11.0 | 22 | 0.6981 | 0.22 | 0.3607 | 1.0 | 0.22 |
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+ | No log | 12.0 | 24 | 0.6962 | 0.22 | 0.3607 | 1.0 | 0.22 |
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+ | No log | 13.0 | 26 | 0.6941 | 0.24 | 0.3871 | 1.0 | 0.24 |
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+ | No log | 14.0 | 28 | 0.6917 | 0.44 | 0.6111 | 1.0 | 0.44 |
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+ | No log | 15.0 | 30 | 0.6893 | 0.58 | 0.7342 | 1.0 | 0.58 |
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+ | No log | 16.0 | 32 | 0.6869 | 0.76 | 0.8636 | 1.0 | 0.76 |
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+ | No log | 17.0 | 34 | 0.6842 | 0.88 | 0.9362 | 1.0 | 0.88 |
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+ | No log | 18.0 | 36 | 0.6816 | 0.9 | 0.9474 | 1.0 | 0.9 |
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+ | No log | 19.0 | 38 | 0.6789 | 0.92 | 0.9583 | 1.0 | 0.92 |
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+ | No log | 20.0 | 40 | 0.6763 | 0.92 | 0.9583 | 1.0 | 0.92 |
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+
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+
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+ ### Framework versions
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+
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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