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--- |
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license: mit |
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tags: |
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- generated_from_keras_callback |
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base_model: facebook/esm2_t30_150M_UR50D |
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model-index: |
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- name: esm2_t30_150M_UR50D-finetuned-AMP_Antibacteria-classification |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# esm2_t30_150M_UR50D-finetuned-AMP_Antibacteria-classification |
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This model is a fine-tuned version of [facebook/esm2_t30_150M_UR50D](https://huggingface.co/facebook/esm2_t30_150M_UR50D) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0433 |
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- Train Accuracy: 0.9871 |
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- Validation Loss: 0.7702 |
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- Validation Accuracy: 0.8014 |
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- Epoch: 19 |
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 0.6498 | 0.6047 | 0.6345 | 0.6288 | 0 | |
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| 0.5714 | 0.6877 | 0.5871 | 0.6882 | 1 | |
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| 0.3898 | 0.8198 | 0.5698 | 0.7242 | 2 | |
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| 0.2481 | 0.8921 | 0.5758 | 0.7696 | 3 | |
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| 0.1838 | 0.9248 | 0.6483 | 0.7730 | 4 | |
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| 0.1475 | 0.9390 | 0.6187 | 0.7904 | 5 | |
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| 0.1147 | 0.9541 | 0.6663 | 0.8007 | 6 | |
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| 0.0948 | 0.9618 | 0.7591 | 0.7819 | 7 | |
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| 0.0800 | 0.9701 | 0.7534 | 0.7959 | 8 | |
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| 0.0709 | 0.9739 | 0.8595 | 0.7810 | 9 | |
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| 0.0629 | 0.9767 | 0.8192 | 0.7907 | 10 | |
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| 0.0578 | 0.9792 | 0.8855 | 0.7946 | 11 | |
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| 0.0532 | 0.9814 | 0.9993 | 0.7762 | 12 | |
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| 0.0586 | 0.9801 | 0.9058 | 0.7761 | 13 | |
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| 0.0534 | 0.9816 | 0.8338 | 0.7786 | 14 | |
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| 0.0508 | 0.9824 | 0.7899 | 0.8033 | 15 | |
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| 0.0472 | 0.9840 | 0.9000 | 0.7800 | 16 | |
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| 0.0441 | 0.9851 | 0.8732 | 0.7911 | 17 | |
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| 0.0486 | 0.9846 | 0.8166 | 0.8088 | 18 | |
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| 0.0433 | 0.9871 | 0.7702 | 0.8014 | 19 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- TensorFlow 2.15.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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