---
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