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README.md
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This model is a ChemBERTa model trained on the augmented_canonical_pubchem_13m dataset.
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The model was trained for
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To improve performance, mixed precision (fp16), TF32, and torch.compile were enabled. Training used gradient accumulation (16 steps) and batch size of 128 for efficient resource utilization.
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Evaluation was performed at regular intervals, with the best model selected based on validation performance.
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This model is a ChemBERTa model trained on the augmented_canonical_pubchem_13m dataset.
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The model was trained for 24 epochs using NVIDIA Apex's FusedAdam optimizer with a reduce-on-plateau learning rate scheduler.
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To improve performance, mixed precision (fp16), TF32, and torch.compile were enabled. Training used gradient accumulation (16 steps) and batch size of 128 for efficient resource utilization.
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Evaluation was performed at regular intervals, with the best model selected based on validation performance.
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