transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:hate_speech18 base_model:agvidit1/DistilledBert_HateSpeech_pretrain base_model:finetune:agvidit1/DistilledBert_HateSpeech_pretrain license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: agvidit1/DistilledBert_HateSpeech_pretrain
datasets:
- hate_speech18
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-hate_speech18
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: hate_speech18
      type: hate_speech18
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.8587751371115173
      name: Accuracy
---

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# distilbert-hate_speech18

This model is a fine-tuned version of [agvidit1/DistilledBert_HateSpeech_pretrain](https://huggingface.co/agvidit1/DistilledBert_HateSpeech_pretrain) on the hate_speech18 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4684
- Accuracy: 0.8588

## 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: 5.050180626898551e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4404        | 1.0   | 240  | 0.4670          | 0.8533   |
| 0.4356        | 2.0   | 480  | 0.4642          | 0.8675   |
| 0.4303        | 3.0   | 720  | 0.4649          | 0.8748   |
| 0.4282        | 4.0   | 960  | 0.4694          | 0.8592   |
| 0.4273        | 5.0   | 1200 | 0.4638          | 0.8729   |
| 0.4256        | 6.0   | 1440 | 0.4651          | 0.8679   |
| 0.425         | 7.0   | 1680 | 0.4682          | 0.8560   |
| 0.4227        | 8.0   | 1920 | 0.4684          | 0.8588   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0
