ESM1b_AAV2_classification

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ESM1b_AAV2_classification

To load tokenizer from ESM, you need to install transformers with this version as follow:

!git clone -b add_esm-proper --single-branch https://github.com/liujas000/transformers.git !pip -q install ./transformers

This model is a fine-tuned version of facebook/esm-1b on AAV2 dataset with ~230k sequences (Bryant et al 2020).

The WT sequence (aa561-588): D E E E I R T T N P V A T E Q Y G S V S T N L Q R G N R Maximum length: 50

It achieves the following results on the evaluation set. Note:this is result of the last epoch, I think the pushed model is loaded with best checkpoint - best val_loss, I'm not so sure though :/

• Loss: 0.2250
• Accuracy: 0.9620
• F1: 0.9632
• Precision: 0.9642
• Recall: 0.9622
• Auroc: 0.9620

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 64
• total_train_batch_size: 1024
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 200
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.13.0.dev0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.10.3