---
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: 0.5742059850477367
---

<!-- 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-tape-fluorescence-evotuning-DistilProtBert

This model is a fine-tuned version of [thundaa/tape-fluorescence-evotuning-DistilProtBert](https://huggingface.co/thundaa/tape-fluorescence-evotuning-DistilProtBert) on the cradle-bio/tape-fluorescence dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2709
- Spearmanr: 0.5742

## 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: 40
- eval_batch_size: 40
- seed: 11
- gradient_accumulation_steps: 64
- total_train_batch_size: 2560
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 6.4382        | 0.93  | 7    | 2.0198          | -0.0244   |
| 1.1243        | 1.93  | 14   | 0.7986          | -0.0083   |
| 0.802         | 2.93  | 21   | 0.6902          | 0.2336    |
| 0.7469        | 3.93  | 28   | 0.6665          | 0.3001    |
| 0.7519        | 4.93  | 35   | 0.6578          | 0.3895    |
| 0.7247        | 5.93  | 42   | 0.6346          | 0.3682    |
| 0.6991        | 6.93  | 49   | 0.8796          | 0.3681    |
| 0.6829        | 7.93  | 56   | 0.6098          | 0.3747    |
| 0.7241        | 8.93  | 63   | 0.7538          | 0.4345    |
| 0.6703        | 9.93  | 70   | 0.5646          | 0.4419    |
| 0.6415        | 10.93 | 77   | 1.6112          | 0.3947    |
| 1.0551        | 11.93 | 84   | 1.9104          | 0.4256    |
| 1.2621        | 12.93 | 91   | 0.5694          | 0.4640    |
| 0.7165        | 13.93 | 98   | 0.5647          | 0.4748    |
| 0.602         | 14.93 | 105  | 0.3979          | 0.4907    |
| 0.4668        | 15.93 | 112  | 0.3896          | 0.4891    |
| 0.5248        | 16.93 | 119  | 0.5101          | 0.4878    |
| 0.6232        | 17.93 | 126  | 0.3298          | 0.5128    |
| 0.5491        | 18.93 | 133  | 0.6220          | 0.5210    |
| 0.5022        | 19.93 | 140  | 0.5351          | 0.5212    |
| 0.7122        | 20.93 | 147  | 0.3773          | 0.5278    |
| 0.377         | 21.93 | 154  | 0.3368          | 0.5278    |
| 0.3689        | 22.93 | 161  | 0.4503          | 0.5266    |
| 0.3768        | 23.93 | 168  | 0.3237          | 0.5428    |
| 0.3308        | 24.93 | 175  | 0.2850          | 0.5559    |
| 0.3182        | 25.93 | 182  | 0.2804          | 0.5611    |
| 0.3135        | 26.93 | 189  | 0.2792          | 0.5660    |
| 0.2953        | 27.93 | 196  | 0.2669          | 0.5707    |
| 0.2917        | 28.93 | 203  | 0.2654          | 0.5742    |
| 0.2652        | 29.93 | 210  | 0.2709          | 0.5742    |


### Framework versions

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