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BERT_newdata-6_tokenized
Mozart-coder/BERT_newdata-6_tokenized
BERT_newdata-6_tokenized is a fill-mask model from Mozart-coder. Use it when you need the model to fill a missing word. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Oct 23, 2022
- Updated
- Oct 23, 2022
- SHA
- 103f822f
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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. -->
BERT_newdata-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: 0.0378
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 |
|---|---|---|---|
| 0.0669 | 1.0 | 223 | 0.0373 |
| 0.0394 | 2.0 | 446 | 0.0398 |
| 0.0369 | 3.0 | 669 | 0.0371 |
| 0.0362 | 4.0 | 892 | 0.0358 |
| 0.0383 | 5.0 | 1115 | 0.0353 |
| 0.0365 | 6.0 | 1338 | 0.0378 |
| 0.0366 | 7.0 | 1561 | 0.0377 |
| 0.0373 | 8.0 | 1784 | 0.0359 |
| 0.0372 | 9.0 | 2007 | 0.0371 |
| 0.0377 | 10.0 | 2230 | 0.0357 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- Created
- Oct 23, 2022
- Updated
- Oct 23, 2022