metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: prot_bert_bfd-disoRNA
results: []
prot_bert_bfd-disoRNA
This model is a fine-tuned version of Rostlab/prot_bert_bfd on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0634
- Precision: 0.9746
- Recall: 0.9872
- F1: 0.9809
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.0627 | 1.0 | 61 | 0.0665 | 0.9746 | 0.9872 | 0.9809 |
| 0.0186 | 2.0 | 122 | 0.0644 | 0.9746 | 0.9872 | 0.9809 |
| 0.015 | 3.0 | 183 | 0.0634 | 0.9746 | 0.9872 | 0.9809 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1