Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AFZALS/ToxicClassification2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AFZALS/ToxicClassification2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AFZALS/ToxicClassification2.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AFZALS/ToxicClassification2.0") model = AutoModelForSequenceClassification.from_pretrained("AFZALS/ToxicClassification2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ToxicClassification2.0
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7477
- Accuracy: 0.8677
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4987 | 1.0 | 970 | 0.3175 | 0.8598 |
| 0.3342 | 2.0 | 1940 | 0.3325 | 0.8692 |
| 0.2808 | 3.0 | 2910 | 0.3273 | 0.8675 |
| 0.2514 | 4.0 | 3880 | 0.3878 | 0.8652 |
| 0.2075 | 5.0 | 4850 | 0.4068 | 0.8611 |
| 0.1887 | 6.0 | 5820 | 0.5277 | 0.8692 |
| 0.1641 | 7.0 | 6790 | 0.6208 | 0.8662 |
| 0.1419 | 8.0 | 7760 | 0.6979 | 0.8698 |
| 0.1150 | 9.0 | 8730 | 0.7489 | 0.8673 |
| 0.1005 | 10.0 | 9700 | 0.7477 | 0.8677 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for AFZALS/ToxicClassification2.0
Base model
FacebookAI/xlm-roberta-base