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# mongolian-roberta-base-mn

This model is a fine-tuned version of [bayartsogt/mongolian-roberta-base](https://huggingface.co/bayartsogt/mongolian-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.9189
- Recall: 0.9301
- F1: 0.9245
- Accuracy: 0.9803

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["mn"], "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "mongolian-roberta-base-mn", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer mn autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #mn #autotrain_compatible #endpoints_compatible #region-us 




# mongolian-roberta-base-mn

This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.9189
- Recall: 0.9301
- F1: 0.9245
- Accuracy: 0.9803

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# mongolian-roberta-base-mn

This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.9189
- Recall: 0.9301
- F1: 0.9245
- Accuracy: 0.9803 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #mn #autotrain_compatible #endpoints_compatible #region-us 
 # mongolian-roberta-base-mn

This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.9189
- Recall: 0.9301
- F1: 0.9245
- Accuracy: 0.9803 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3