
<!-- 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 [](https://huggingface.co/) 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

{"tags": ["generated_from_trainer"], "model-index": [{"name": "DNADebertaBPE10k", "results": []}]}
transformers pytorch tensorboard deberta fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #deberta #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# DNADebertaBPE10k

This model is a fine-tuned version of [](URL 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

# DNADebertaBPE10k

This model is a fine-tuned version of [](URL 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
TAGS
#transformers #pytorch #tensorboard #deberta #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # DNADebertaBPE10k

This model is a fine-tuned version of [](URL 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
passage: TAGS
#transformers #pytorch #tensorboard #deberta #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# DNADebertaBPE10k

This model is a fine-tuned version of [](URL 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