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# model_category_dataset_hate_speech_epoch_lr_1e5

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1548
- Accuracy: 0.9407
- Macro F1: 0.9406
- Micro F1: 0.9407
- Weighted F1: 0.9406
- Precision: 0.9433
- Recall: 0.9407

## 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: 1e-05
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Micro F1 | Weighted F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:-----------:|:---------:|:------:|
| No log        | 1.0   | 47   | 0.3266          | 0.8417   | 0.8415   | 0.8417   | 0.8415      | 0.8433    | 0.8417 |
| No log        | 2.0   | 94   | 0.1669          | 0.9404   | 0.9403   | 0.9404   | 0.9403      | 0.9440    | 0.9404 |
| No log        | 3.0   | 141  | 0.1345          | 0.9545   | 0.9545   | 0.9545   | 0.9545      | 0.9559    | 0.9545 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "base_model": "roberta-base", "model-index": [{"name": "model_category_dataset_hate_speech_epoch_lr_1e5", "results": []}]}
transformers safetensors roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us