|
--- |
|
license: apache-2.0 |
|
tags: |
|
- protein language model |
|
- generated_from_trainer |
|
datasets: |
|
- train |
|
metrics: |
|
- spearmanr |
|
model-index: |
|
- name: tape-fluorescence-prediction-tape-fluorescence-evotuning-DistilProtBert |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: cradle-bio/tape-fluorescence |
|
type: train |
|
metrics: |
|
- name: Spearmanr |
|
type: spearmanr |
|
value: 0.6085202769301487 |
|
--- |
|
|
|
<!-- 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-tape-fluorescence-evotuning-DistilProtBert |
|
|
|
This model is a fine-tuned version of [thundaa/tape-fluorescence-evotuning-DistilProtBert](https://huggingface.co/thundaa/tape-fluorescence-evotuning-DistilProtBert) on the cradle-bio/tape-fluorescence dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2716 |
|
- Spearmanr: 0.6085 |
|
|
|
## 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: 40 |
|
- eval_batch_size: 40 |
|
- seed: 17 |
|
- gradient_accumulation_steps: 64 |
|
- total_train_batch_size: 2560 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Spearmanr | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:| |
|
| 5.9308 | 0.93 | 7 | 1.6932 | 0.0822 | |
|
| 1.0148 | 1.93 | 14 | 0.7407 | 0.1233 | |
|
| 0.7748 | 2.93 | 21 | 0.7388 | 0.3237 | |
|
| 0.7444 | 3.93 | 28 | 0.8205 | 0.4712 | |
|
| 0.7623 | 4.93 | 35 | 0.7168 | 0.4582 | |
|
| 0.7117 | 5.93 | 42 | 0.6898 | 0.4839 | |
|
| 0.7987 | 6.93 | 49 | 1.1860 | 0.3994 | |
|
| 0.8235 | 7.93 | 56 | 0.7290 | 0.4122 | |
|
| 1.0447 | 8.93 | 63 | 1.8475 | 0.4169 | |
|
| 0.9244 | 9.93 | 70 | 0.8985 | 0.4361 | |
|
| 0.7392 | 10.93 | 77 | 0.7053 | 0.4709 | |
|
| 0.5879 | 11.93 | 84 | 0.4930 | 0.4761 | |
|
| 0.5723 | 12.93 | 91 | 0.9298 | 0.4765 | |
|
| 0.7221 | 13.93 | 98 | 0.9479 | 0.4866 | |
|
| 1.0731 | 14.93 | 105 | 0.5306 | 0.5040 | |
|
| 0.5242 | 15.93 | 112 | 0.6331 | 0.4938 | |
|
| 0.5606 | 16.93 | 119 | 0.4096 | 0.5060 | |
|
| 0.5314 | 17.93 | 126 | 0.5781 | 0.5130 | |
|
| 0.4384 | 18.93 | 133 | 0.3880 | 0.5393 | |
|
| 0.4117 | 19.93 | 140 | 0.4584 | 0.5504 | |
|
| 0.4387 | 20.93 | 147 | 0.3611 | 0.5674 | |
|
| 0.3613 | 21.93 | 154 | 0.4159 | 0.5806 | |
|
| 0.5157 | 22.93 | 161 | 0.4041 | 0.5869 | |
|
| 0.4049 | 23.93 | 168 | 0.3187 | 0.5888 | |
|
| 0.3318 | 24.93 | 175 | 0.3206 | 0.5889 | |
|
| 0.3317 | 25.93 | 182 | 0.2964 | 0.5941 | |
|
| 0.303 | 26.93 | 189 | 0.2803 | 0.6006 | |
|
| 0.3058 | 27.93 | 196 | 0.2758 | 0.6042 | |
|
| 0.2988 | 28.93 | 203 | 0.3016 | 0.6049 | |
|
| 0.2814 | 29.93 | 210 | 0.2716 | 0.6085 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.11.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
