---
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: 0.6081143924159805
---

<!-- 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: 0.2209
- Spearmanr: 0.6081

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 6.3796        | 0.93  | 7    | 2.2462          | 0.2021    |
| 1.2421        | 1.93  | 14   | 0.7066          | 0.1024    |
| 0.7978        | 2.93  | 21   | 0.6895          | 0.1444    |
| 0.7613        | 3.93  | 28   | 0.6758          | 0.2527    |
| 0.7498        | 4.93  | 35   | 0.6772          | 0.2620    |
| 0.7486        | 5.93  | 42   | 0.6703          | 0.3991    |
| 0.7394        | 6.93  | 49   | 0.6506          | 0.4038    |
| 0.8251        | 7.93  | 56   | 1.3414          | 0.3358    |
| 0.8479        | 8.93  | 63   | 0.6745          | 0.3353    |
| 0.7954        | 9.93  | 70   | 0.6610          | 0.4157    |
| 0.7316        | 10.93 | 77   | 0.4977          | 0.4483    |
| 0.6027        | 11.93 | 84   | 0.4138          | 0.4517    |
| 0.5239        | 12.93 | 91   | 0.4185          | 0.4798    |
| 0.4802        | 13.93 | 98   | 0.3637          | 0.5082    |
| 0.5417        | 14.93 | 105  | 0.3360          | 0.5143    |
| 0.5022        | 15.93 | 112  | 0.5404          | 0.5207    |
| 0.4487        | 16.93 | 119  | 0.4884          | 0.5347    |
| 0.4229        | 17.93 | 126  | 0.2941          | 0.5530    |
| 0.3785        | 18.93 | 133  | 0.2920          | 0.5625    |
| 0.3448        | 19.93 | 140  | 0.3082          | 0.5589    |
| 0.3352        | 20.93 | 147  | 0.3006          | 0.5638    |
| 0.3219        | 21.93 | 154  | 0.2707          | 0.5737    |
| 0.3156        | 22.93 | 161  | 0.2623          | 0.5775    |
| 0.3142        | 23.93 | 168  | 0.3162          | 0.5752    |
| 0.3003        | 24.93 | 175  | 0.2487          | 0.5897    |
| 0.303         | 25.93 | 182  | 0.2633          | 0.5981    |
| 0.2757        | 26.93 | 189  | 0.2813          | 0.5921    |
| 0.2836        | 27.93 | 196  | 0.2696          | 0.5968    |
| 0.2759        | 28.93 | 203  | 0.2230          | 0.6060    |
| 0.232         | 29.93 | 210  | 0.2209          | 0.6081    |


### Framework versions

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