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README.md
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---
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license: apache-2.0
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tags:
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- protein language model
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- generated_from_trainer
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datasets:
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- train
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metrics:
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- spearmanr
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model-index:
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- name: tape-fluorescence-prediction-RITA_s
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: cradle-bio/tape-fluorescence
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type: train
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metrics:
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- name: Spearmanr
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type: spearmanr
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value: 0.22463833322952328
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# tape-fluorescence-prediction-RITA_s
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This model is a fine-tuned version of [lightonai/RITA_s](https://huggingface.co/lightonai/RITA_s) on the cradle-bio/tape-fluorescence dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6701
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- Spearmanr: 0.2246
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 128
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- total_train_batch_size: 4096
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 15
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|
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| 6.8975 | 0.85 | 4 | 0.7033 | -0.0855 |
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| 1.2475 | 1.85 | 8 | 0.7764 | 0.0752 |
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| 0.934 | 2.85 | 12 | 0.6740 | 0.0423 |
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| 0.8294 | 3.85 | 16 | 0.6732 | 0.1257 |
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| 0.8274 | 4.85 | 20 | 0.6826 | 0.1877 |
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| 0.8333 | 5.85 | 24 | 0.6838 | 0.1494 |
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| 0.8287 | 6.85 | 28 | 0.6800 | 0.1292 |
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| 0.8278 | 7.85 | 32 | 0.6777 | 0.1293 |
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| 0.8267 | 8.85 | 36 | 0.6749 | 0.1349 |
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| 0.8275 | 9.85 | 40 | 0.6794 | 0.1942 |
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| 0.8276 | 10.85 | 44 | 0.6728 | 0.1639 |
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| 0.8245 | 11.85 | 48 | 0.6721 | 0.1776 |
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| 0.823 | 12.85 | 52 | 0.6715 | 0.1874 |
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| 0.822 | 13.85 | 56 | 0.6707 | 0.1731 |
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| 0.7005 | 14.85 | 60 | 0.6701 | 0.2246 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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