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@@ -25,8 +25,9 @@ trained on `166` protein sequences in the [RNA binding sites dataset](https://hu
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  using a `85/15` train/test split. This model was trained with class weighting due to the imbalanced nature
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  of the RNA binding site dataset (fewer binding sites than non-binding sites). This model has slightly improved
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  precision, recall, and F1 score over [AmelieSchreiber/esm2_t12_35M_weighted_lora_rna_binding](https://huggingface.co/AmelieSchreiber/esm2_t12_35M_weighted_lora_rna_binding)
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- but may suffer from mild overfitting, as indicated by the training loss being slightly lower than the eval loss. If you are searching for
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- binding sites and aren't worried about false positives, the higher recall may make this model preferable to the other RNA binding site predictors.
 
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  You can train your own version
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  using [this notebook](https://huggingface.co/AmelieSchreiber/esm2_t6_8M_weighted_lora_rna_binding/blob/main/LoRA_binding_sites_no_sweeps_v2.ipynb)!
 
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  using a `85/15` train/test split. This model was trained with class weighting due to the imbalanced nature
26
  of the RNA binding site dataset (fewer binding sites than non-binding sites). This model has slightly improved
27
  precision, recall, and F1 score over [AmelieSchreiber/esm2_t12_35M_weighted_lora_rna_binding](https://huggingface.co/AmelieSchreiber/esm2_t12_35M_weighted_lora_rna_binding)
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+ but may suffer from mild overfitting, as indicated by the training loss being slightly lower than the eval loss (see metrics below).
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+ If you are searching for binding sites and aren't worried about false positives, the higher recall may make this model
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+ preferable to the other RNA binding site predictors.
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  You can train your own version
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  using [this notebook](https://huggingface.co/AmelieSchreiber/esm2_t6_8M_weighted_lora_rna_binding/blob/main/LoRA_binding_sites_no_sweeps_v2.ipynb)!