README.md

metadata

license: apache-2.0
tags:
  - protein language model
  - generated_from_trainer
datasets:
  - train
metrics:
  - spearmanr
model-index:
  - name: tape-fluorescence-prediction-tape-fluorescence-evotuning-DistilProtBert
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: cradle-bio/tape-fluorescence
          type: train
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.23980333080780145

tape-fluorescence-prediction-tape-fluorescence-evotuning-DistilProtBert

This model is a fine-tuned version of thundaa/tape-fluorescence-evotuning-DistilProtBert on the cradle-bio/tape-fluorescence dataset. It achieves the following results on the evaluation set:

• Loss: 0.6838
• Spearmanr: 0.2398

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 128
• total_train_batch_size: 4096
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Spearmanr
9.0167	0.85	4	4.9224	-0.0084
4.0263	1.85	8	2.0909	0.0824
1.7616	2.85	12	0.9869	0.1583
0.9814	3.85	16	0.7071	0.2798
0.7082	4.85	20	0.6838	0.2398

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1