transformers pytorch roberta text-classification generated_from_trainer dataset:tweets_hate_speech_detection license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- tweets_hate_speech_detection
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: FirstTry
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweets_hate_speech_detection
      type: tweets_hate_speech_detection
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.9821679962458939
      name: Accuracy
    - type: f1
      value: 0.8692660550458716
      name: F1
---

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# FirstTry

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the tweets_hate_speech_detection dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0847
- Accuracy: 0.9822
- F1: 0.8693

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1159        | 1.0   | 1599 | 0.1019          | 0.9759   | 0.8270 |
| 0.0727        | 2.0   | 3198 | 0.0965          | 0.9795   | 0.8424 |
| 0.044         | 3.0   | 4797 | 0.0847          | 0.9822   | 0.8693 |
| 0.0301        | 4.0   | 6396 | 0.1121          | 0.9811   | 0.8660 |
| 0.0206        | 5.0   | 7995 | 0.1718          | 0.9700   | 0.8110 |
| 0.0176        | 6.0   | 9594 | 0.1453          | 0.9811   | 0.8591 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.10.1
- Tokenizers 0.13.3
