Text Classification
Transformers
TensorFlow
English
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use ZachBeesley/toxic-comments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZachBeesley/toxic-comments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZachBeesley/toxic-comments")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ZachBeesley/toxic-comments") model = AutoModelForSequenceClassification.from_pretrained("ZachBeesley/toxic-comments") - Notebooks
- Google Colab
- Kaggle
ZachBeesley/toxic-comments
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0563
- Epoch: 1
Model description
Text-classification model that can classify whether a piece of text is toxic or not
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 29919, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Epoch |
|---|---|
| 0.0909 | 0 |
| 0.0563 | 1 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
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Model tree for ZachBeesley/toxic-comments
Base model
distilbert/distilbert-base-uncased