readme: ---
  license: apache-2.0
  tags:
  - protein language model
  - generated_from_trainer
  datasets:
  - train
  metrics:
  - spearmanr
  model-index:
  - name: tape-fluorescence-prediction-RITA_s
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: cradle-bio/tape-fluorescence
        type: train
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.2955275250425323
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # tape-fluorescence-prediction-RITA_s
  
  This model is a fine-tuned version of [lightonai/RITA_s](https://huggingface.co/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
  