metadata
tags:
- generated_from_trainer
model-index:
- name: BERT_full_data3-6_tokenized
results: []
BERT_full_data3-6_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: 0.0370
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0649 | 1.0 | 284 | 0.0381 |
| 0.0401 | 2.0 | 568 | 0.0364 |
| 0.0374 | 3.0 | 852 | 0.0371 |
| 0.0371 | 4.0 | 1136 | 0.0352 |
| 0.0365 | 5.0 | 1420 | 0.0360 |
| 0.0353 | 6.0 | 1704 | 0.0375 |
| 0.0353 | 7.0 | 1988 | 0.0357 |
| 0.0364 | 8.0 | 2272 | 0.0349 |
| 0.0353 | 9.0 | 2556 | 0.0343 |
| 0.0356 | 10.0 | 2840 | 0.0345 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1