metadata
tags:
- generated_from_trainer
model-index:
- name: BERT_Feb-6_tokenized
results: []
BERT_Feb-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: 0.0043
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 |
|---|---|---|---|
| 0.0575 | 1.0 | 265 | 0.0237 |
| 0.02 | 2.0 | 530 | 0.0131 |
| 0.0123 | 3.0 | 795 | 0.0086 |
| 0.0103 | 4.0 | 1060 | 0.0071 |
| 0.0078 | 5.0 | 1325 | 0.0061 |
| 0.007 | 6.0 | 1590 | 0.0047 |
| 0.006 | 7.0 | 1855 | 0.0035 |
| 0.006 | 8.0 | 2120 | 0.0043 |
| 0.0051 | 9.0 | 2385 | 0.0043 |
| 0.0057 | 10.0 | 2650 | 0.0038 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1