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license: cc-by-4.0 |
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Mirror of OpenFold parameters as provided in https://github.com/aqlaboratory/openfold. Stopgap solution as the original download link was down. All rights to the authors. |
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OpenFold model parameters, v. 06_22. |
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# Training details: |
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Trained using OpenFold on 44 A100s using the training schedule from Table 4 in |
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the AlphaFold supplement. AlphaFold was used as the pre-distillation model. |
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Training data is hosted publicly in the "OpenFold Training Data" RODA repository. |
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# Parameter files: |
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Parameter files fall into the following categories: |
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initial_training.pt: |
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OpenFold at the end of the initial training phase. |
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finetuning_x.pt: |
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Checkpoints in chronological order corresponding to peaks in the |
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validation LDDT-Ca during the finetuning phase. Roughly evenly spaced |
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across the 45 finetuning epochs. |
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finetuning_ptm_x.pt: |
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Checkpoints in chronological order corresponding to peaks inthe pTM |
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training phase, a short additional training phase that takes place |
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after finetuning. Models in this category include the pTM module and |
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comprise the most recent of the checkpoints in this directory. |
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Average validation LDDT-Ca scores for each of the checkpoints are listed below. |
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The validation set contains approximately 180 chains drawn from CAMEO over a |
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three-month period at the end of 2021. |
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initial_training: 0.9088 |
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finetuning_ptm_1: 0.9075 |
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finetuning_ptm_2: 0.9097 |
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finetuning_1: 0.9089 |
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finetuning_2: 0.9061 |
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finetuning_3: 0.9075 |
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finetuning_4: 0.9059 |
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finetuning_5: 0.9054 |
