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--- |
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license: mit |
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base_model: facebook/esm2_t30_150M_UR50D |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: esm2_t30_150M_UR50D-finetuned-SO2F |
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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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# esm2_t30_150M_UR50D-finetuned-SO2F |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6608 |
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- Accuracy: 0.7158 |
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- Precision: 0.1682 |
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- Recall: 0.5068 |
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- F1: 0.2526 |
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- Auc: 0.6223 |
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- Mcc: 0.1585 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | Mcc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:------:| |
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| No log | 1.0 | 108 | 0.6768 | 0.6886 | 0.1465 | 0.4740 | 0.2238 | 0.5925 | 0.1175 | |
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| No log | 2.0 | 216 | 0.6646 | 0.6935 | 0.1628 | 0.5397 | 0.2502 | 0.6247 | 0.1573 | |
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| No log | 3.0 | 324 | 0.6608 | 0.7158 | 0.1682 | 0.5068 | 0.2526 | 0.6223 | 0.1585 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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