metadata
base_model: Rostlab/prot_bert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: prot_bert-finetuned-15ALL_TR
results: []
prot_bert-finetuned-15ALL_TR
This model is a fine-tuned version of Rostlab/prot_bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6087
- Accuracy: 0.6696
- F1: 0.6689
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6715 | 1.0 | 186 | 0.6318 | 0.6528 | 0.6507 |
| 0.5998 | 2.0 | 372 | 0.6087 | 0.6696 | 0.6689 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2