metadata
tags:
- generated_from_trainer
model-index:
- name: BERT_full-6_tokenized
results: []
BERT_full-6_tokenized
This model is a fine-tuned version of armheb/DNA_bert_6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0362
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: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0775 | 1.0 | 284 | 0.0411 |
| 0.0428 | 2.0 | 568 | 0.0393 |
| 0.0395 | 3.0 | 852 | 0.0396 |
| 0.0395 | 4.0 | 1136 | 0.0374 |
| 0.0379 | 5.0 | 1420 | 0.0379 |
| 0.037 | 6.0 | 1704 | 0.0399 |
| 0.0368 | 7.0 | 1988 | 0.0382 |
| 0.0378 | 8.0 | 2272 | 0.0378 |
| 0.0365 | 9.0 | 2556 | 0.0362 |
| 0.0374 | 10.0 | 2840 | 0.0359 |
| 0.0372 | 11.0 | 3124 | 0.0373 |
| 0.0358 | 12.0 | 3408 | 0.0378 |
| 0.0361 | 13.0 | 3692 | 0.0385 |
| 0.0364 | 14.0 | 3976 | 0.0383 |
| 0.035 | 15.0 | 4260 | 0.0376 |
| 0.035 | 16.0 | 4544 | 0.0376 |
| 0.036 | 17.0 | 4828 | 0.0388 |
| 0.0365 | 18.0 | 5112 | 0.0372 |
| 0.0355 | 19.0 | 5396 | 0.0363 |
| 0.0349 | 20.0 | 5680 | 0.0378 |
| 0.0345 | 21.0 | 5964 | 0.0377 |
| 0.0349 | 22.0 | 6248 | 0.0372 |
| 0.035 | 23.0 | 6532 | 0.0374 |
| 0.0351 | 24.0 | 6816 | 0.0379 |
| 0.0351 | 25.0 | 7100 | 0.0374 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1