metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: Electra_Hatespeech_Classifier5
results: []
Electra_Hatespeech_Classifier5
This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2370
- F1: 0.9484
- Accuracy: 0.9629
- Precision: 0.9540
- Recall: 0.9428
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: 8
- seed: 100
- 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 | F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2066 | 1.0 | 5084 | 0.2209 | 0.8904 | 0.9180 | 0.8624 | 0.9204 |
| 0.1319 | 2.0 | 10168 | 0.1719 | 0.9290 | 0.9490 | 0.9363 | 0.9218 |
| 0.0785 | 3.0 | 15252 | 0.2224 | 0.9409 | 0.9582 | 0.9617 | 0.9211 |
| 0.0365 | 4.0 | 20336 | 0.2370 | 0.9484 | 0.9629 | 0.9540 | 0.9428 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2