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# MARBERT-adept

This model is a fine-tuned version of [UBC-NLP/MARBERT](https://huggingface.co/UBC-NLP/MARBERT) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6149
- eval_runtime: 323.5555
- eval_samples_per_second: 34.615
- eval_steps_per_second: 4.327
- step: 0

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

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




# MARBERT-adept

This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6149
- eval_runtime: 323.5555
- eval_samples_per_second: 34.615
- eval_steps_per_second: 4.327
- step: 0

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

# MARBERT-adept

This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6149
- eval_runtime: 323.5555
- eval_samples_per_second: 34.615
- eval_steps_per_second: 4.327
- step: 0 ## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # MARBERT-adept

This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6149
- eval_runtime: 323.5555
- eval_samples_per_second: 34.615
- eval_steps_per_second: 4.327
- step: 0 ## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# MARBERT-adept

This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6149
- eval_runtime: 323.5555
- eval_samples_per_second: 34.615
- eval_steps_per_second: 4.327
- step: 0## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1