---
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: 0.32362885705173594
---

<!-- 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: 0.7029
- Spearmanr: 0.3236

## 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: 17
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.0854        | 0.85  | 4    | 0.8055          | 0.0686    |
| 0.8791        | 1.85  | 8    | 0.7455          | 0.1288    |
| 0.822         | 2.85  | 12   | 0.7385          | 0.2069    |
| 0.8155        | 3.85  | 16   | 0.7346          | 0.2680    |
| 0.8139        | 4.85  | 20   | 0.7345          | 0.3102    |
| 0.81          | 5.85  | 24   | 0.7375          | 0.3349    |
| 0.805         | 6.85  | 28   | 0.7211          | 0.3298    |
| 0.799         | 7.85  | 32   | 0.7114          | 0.3282    |
| 0.784         | 8.85  | 36   | 0.7132          | 0.3220    |
| 0.6627        | 9.85  | 40   | 0.7029          | 0.3236    |


### Framework versions

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