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---
tags:
- generated_from_trainer
metrics:
- spearmanr
model-index:
- name: thermo-predictor-thermo-evotuning-prot_bert
results: []
---
<!-- 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. -->
# thermo-predictor-thermo-evotuning-prot_bert
This model is a fine-tuned version of [thundaa/thermo-evotuning-prot_bert](https://huggingface.co/thundaa/thermo-evotuning-prot_bert) on the cradle-bio/tape-thermostability dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1617
- Spearmanr: 0.6914
## 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: 4e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 16384
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.4734 | 0.68 | 2 | 0.3146 | 0.3359 |
| 0.4392 | 1.68 | 4 | 0.2936 | 0.3407 |
| 0.4034 | 2.68 | 6 | 0.2633 | 0.3696 |
| 0.3669 | 3.68 | 8 | 0.2437 | 0.3903 |
| 0.3496 | 4.68 | 10 | 0.2377 | 0.4102 |
| 0.3351 | 5.68 | 12 | 0.2285 | 0.4204 |
| 0.3289 | 6.68 | 14 | 0.2267 | 0.4180 |
| 0.3267 | 7.68 | 16 | 0.2258 | 0.4242 |
| 0.3177 | 8.68 | 18 | 0.2206 | 0.4295 |
| 0.3116 | 9.68 | 20 | 0.2150 | 0.4365 |
| 0.3039 | 10.68 | 22 | 0.2115 | 0.4365 |
| 0.2985 | 11.68 | 24 | 0.2062 | 0.4469 |
| 0.2927 | 12.68 | 26 | 0.2045 | 0.4531 |
| 0.2885 | 13.68 | 28 | 0.2005 | 0.4603 |
| 0.2838 | 14.68 | 30 | 0.1987 | 0.4690 |
| 0.2806 | 15.68 | 32 | 0.1975 | 0.4744 |
| 0.2772 | 16.68 | 34 | 0.1970 | 0.4765 |
| 0.2728 | 17.68 | 36 | 0.1939 | 0.4845 |
| 0.2684 | 18.68 | 38 | 0.1931 | 0.4858 |
| 0.2641 | 19.68 | 40 | 0.1925 | 0.4936 |
| 0.2608 | 20.68 | 42 | 0.1905 | 0.4929 |
| 0.2566 | 21.68 | 44 | 0.1886 | 0.5049 |
| 0.2518 | 22.68 | 46 | 0.1875 | 0.5095 |
| 0.2467 | 23.68 | 48 | 0.1869 | 0.5141 |
| 0.2424 | 24.68 | 50 | 0.1859 | 0.5161 |
| 0.2375 | 25.68 | 52 | 0.1850 | 0.5223 |
| 0.2329 | 26.68 | 54 | 0.1851 | 0.5210 |
| 0.2279 | 27.68 | 56 | 0.1850 | 0.5294 |
| 0.2226 | 28.68 | 58 | 0.1837 | 0.5310 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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