metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: prot_bert_bfd
results: []
prot_bert_bfd
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5239
- Precision: 0.0334
- Recall: 0.0425
- F1: 0.0374
- Accuracy: 0.7798
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 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 61 | 0.5012 | 0.0392 | 0.0490 | 0.0435 | 0.7649 |
| No log | 2.0 | 122 | 0.4769 | 0.0265 | 0.0458 | 0.0336 | 0.7860 |
| No log | 3.0 | 183 | 0.5239 | 0.0334 | 0.0425 | 0.0374 | 0.7798 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1