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# distilbert-finetuning-hate-speech-score-all-samples-3splits-seedv2-dropout005-epochs-10

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Mse: 0.3501
- Rmse: 0.5917
- Mae: 0.2542
- R2: 0.9374

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-finetuning-hate-speech-score-all-samples-3splits-seedv2-dropout005-epochs-10", "results": []}]}
transformers pytorch tensorboard distilbert generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #generated_from_trainer #endpoints_compatible #region-us 




# distilbert-finetuning-hate-speech-score-all-samples-3splits-seedv2-dropout005-epochs-10

This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Mse: 0.3501
- Rmse: 0.5917
- Mae: 0.2542
- R2: 0.9374

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# distilbert-finetuning-hate-speech-score-all-samples-3splits-seedv2-dropout005-epochs-10

This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Mse: 0.3501
- Rmse: 0.5917
- Mae: 0.2542
- R2: 0.9374 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #distilbert #generated_from_trainer #endpoints_compatible #region-us 
 # distilbert-finetuning-hate-speech-score-all-samples-3splits-seedv2-dropout005-epochs-10

This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Mse: 0.3501
- Rmse: 0.5917
- Mae: 0.2542
- R2: 0.9374 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3