Edit model card

tape-fluorescence-prediction-RITA_s

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

  • Loss: 0.5855
  • Spearmanr: 0.2955

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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Spearmanr
4.3595 0.85 4 0.7057 0.0940
0.8654 1.85 8 0.6873 0.1280
0.8292 2.85 12 0.6835 0.2290
0.8212 3.85 16 0.6837 0.3110
0.8191 4.85 20 0.6799 0.3281
0.8137 5.85 24 0.6748 0.3277
0.8057 6.85 28 0.6592 0.3162
0.7769 7.85 32 0.6283 0.3065
0.7382 8.85 36 0.6103 0.2795
0.5991 9.85 40 0.5855 0.2955

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
Downloads last month
2
Inference Examples
Inference API (serverless) does not yet support model repos that contain custom code.

Evaluation results