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# labse-rutoxicity-classification

This model is a fine-tuned version of [rasa/LaBSE](https://huggingface.co/rasa/LaBSE) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1995
- Acc: 0.9218

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results



### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "labse-rutoxicity-classification", "results": []}]}
tensorboard generated_from_trainer region:us
TAGS
#tensorboard #generated_from_trainer #region-us 




# labse-rutoxicity-classification

This model is a fine-tuned version of rasa/LaBSE on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1995
- Acc: 0.9218

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results



### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

# labse-rutoxicity-classification

This model is a fine-tuned version of rasa/LaBSE on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1995
- Acc: 0.9218 ## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6 ### Training results ### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#tensorboard #generated_from_trainer #region-us 
 # labse-rutoxicity-classification

This model is a fine-tuned version of rasa/LaBSE on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1995
- Acc: 0.9218 ## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6 ### Training results ### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
passage: TAGS
#tensorboard #generated_from_trainer #region-us 
# labse-rutoxicity-classification

This model is a fine-tuned version of rasa/LaBSE on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1995
- Acc: 0.9218## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6### Training results### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1