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---
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
|