README.md

metadata

license: apache-2.0
base_model: agvidit1/GoogleTinyBert_HateSpeech_pretrain
tags:
  - generated_from_trainer
datasets:
  - hate_speech18
metrics:
  - accuracy
model-index:
  - name: berttiny-hate_speech18-bothpretrained
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: hate_speech18
          type: hate_speech18
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.879798903107861

berttiny-hate_speech18-bothpretrained

This model is a fine-tuned version of agvidit1/GoogleTinyBert_HateSpeech_pretrain on the hate_speech18 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4682
• Accuracy: 0.8798

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: 7.12739424754752e-05
• train_batch_size: 16
• eval_batch_size: 128
• seed: 34
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4804	1.0	479	0.4778	0.8624
0.4592	2.0	958	0.4688	0.8761
0.4471	3.0	1437	0.4681	0.8780
0.4405	4.0	1916	0.4682	0.8798

Framework versions

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