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DNADebertaBPE10k
simecek/DNADebertaBPE10k
DNADebertaBPE10k is a fill-mask model from simecek. 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
- deberta
- Access
- Public
- Created
- Jul 14, 2022
- Updated
- Jul 15, 2022
- SHA
- b8fec7d2
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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. -->
DNADebertaBPE10k
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 4.7323
- eval_runtime: 283.5074
- eval_samples_per_second: 394.223
- eval_steps_per_second: 24.641
- epoch: 7.43
- step: 116731
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Fill-Mask
- Library
- transformers
- Type
- deberta
- Created
- Jul 14, 2022
- Updated
- Jul 15, 2022