pytorch tensorboard bert text-classification transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
model-index:
- name: dnabertregressor
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# dnabertregressor

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1368
- Mae: 0.0812
- R2: 0.7815

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mae    | R2     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 402  | 0.2486          | 0.1346 | 0.4418 |
| 0.3662        | 2.0   | 804  | 0.1716          | 0.0969 | 0.7091 |
| 0.1746        | 3.0   | 1206 | 0.1509          | 0.0884 | 0.7573 |
| 0.1305        | 4.0   | 1608 | 0.1443          | 0.0850 | 0.7752 |
| 0.1088        | 5.0   | 2010 | 0.1403          | 0.0830 | 0.7740 |
| 0.1088        | 6.0   | 2412 | 0.1368          | 0.0812 | 0.7815 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1
