File size: 2,156 Bytes
090dafb 55d6d07 090dafb 55d6d07 090dafb 55d6d07 090dafb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
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: 0.23980333080780145
---
<!-- 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: 0.6838
- Spearmanr: 0.2398
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 9.0167 | 0.85 | 4 | 4.9224 | -0.0084 |
| 4.0263 | 1.85 | 8 | 2.0909 | 0.0824 |
| 1.7616 | 2.85 | 12 | 0.9869 | 0.1583 |
| 0.9814 | 3.85 | 16 | 0.7071 | 0.2798 |
| 0.7082 | 4.85 | 20 | 0.6838 | 0.2398 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
|