Downloads · 30 days
38
10% of all-time downloads
DNABert_K6_G_quad_3
roa7n/DNABert_K6_G_quad_3
DNABert_K6_G_quad_3 is a text classification model from roa7n. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
383
Public
Repo size
20.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin357 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Oct 28, 2022
- Updated
- Oct 28, 2022
- SHA
- 8bf4b36d
Try a prompt
Model card
From the Hugging Face model README
<!-- 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. -->
DNABert_K6_G_quad_3
This model is a fine-tuned version of armheb/DNA_bert_6 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0722
- Accuracy: 0.9761
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0912 | 1.0 | 9375 | 0.0883 | 0.9707 |
| 0.0668 | 2.0 | 18750 | 0.0723 | 0.9757 |
| 0.0598 | 3.0 | 28125 | 0.0722 | 0.9761 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Oct 28, 2022
- Updated
- Oct 28, 2022