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# test-mlm

This model is a fine-tuned version of [/root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt](https://huggingface.co//root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.7285

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "test-mlm", "results": []}]}
transformers pytorch deberta-v2 fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# test-mlm

This model is a fine-tuned version of /root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.7285

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

# test-mlm

This model is a fine-tuned version of /root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.7285 ## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #deberta-v2 #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # test-mlm

This model is a fine-tuned version of /root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.7285 ## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #deberta-v2 #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# test-mlm

This model is a fine-tuned version of /root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3251
- Accuracy: 0.7285## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1