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# Misogynistic statements classification model

**Model that classifies text as sexist or non-sexist.**

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the [misogynistic-statements-classification dataset](https://huggingface.co/datasets/glombardo/misogynistic-statements-classification).
It achieves the following results on the evaluation set:
- Loss: 0.2493
- Accuracy: 0.9524

## 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: 5e-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: 3

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
{"language": ["es"], "license": "apache-2.0", "tags": ["text-classification", "generated_from_trainer"], "datasets": ["glombardo/misogynistic-statements-classification"], "metrics": ["accuracy"], "widget": [{"text": "Las mujeres deben ser madres antes que nada", "example_title": "Machista"}, {"text": "Las mujeres tienen el mismo potencial y habilidades para los negocios que los hombres", "example_title": "No machista"}], "output_data": [{"format": "class"}, {"class_labels": ["Sexist", "Non-sexist"]}], "model-index": [{"name": "misogynistic-statements-classification-model", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer es dataset:glombardo/misogynistic-statements-classification license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #es #dataset-glombardo/misogynistic-statements-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# Misogynistic statements classification model

Model that classifies text as sexist or non-sexist.

This model is a fine-tuned version of distilroberta-base on the misogynistic-statements-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2493
- Accuracy: 0.9524

## 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: 5e-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: 3

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
# Misogynistic statements classification model

Model that classifies text as sexist or non-sexist.

This model is a fine-tuned version of distilroberta-base on the misogynistic-statements-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2493
- Accuracy: 0.9524 ## 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: 5e-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: 3 ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #es #dataset-glombardo/misogynistic-statements-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Misogynistic statements classification model

Model that classifies text as sexist or non-sexist.

This model is a fine-tuned version of distilroberta-base on the misogynistic-statements-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2493
- Accuracy: 0.9524 ## 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: 5e-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: 3 ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3