Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use hawalurahman/xlm-roberta-base-difficulty-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hawalurahman/xlm-roberta-base-difficulty-prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hawalurahman/xlm-roberta-base-difficulty-prediction")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hawalurahman/xlm-roberta-base-difficulty-prediction") model = AutoModelForSequenceClassification.from_pretrained("hawalurahman/xlm-roberta-base-difficulty-prediction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
xlm-roberta-base-difficulty-prediction
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9634
- Accuracy: 0.5765
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: 5e-06
- 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 |
|---|---|---|---|---|
| 1.0604 | 1.0 | 35 | 0.9769 | 0.6 |
| 0.997 | 2.0 | 70 | 0.9126 | 0.6 |
| 0.9432 | 3.0 | 105 | 0.8917 | 0.5765 |
| 0.8816 | 4.0 | 140 | 0.8931 | 0.4824 |
| 0.8425 | 5.0 | 175 | 0.9101 | 0.5412 |
| 0.7754 | 6.0 | 210 | 0.8895 | 0.6353 |
| 0.732 | 7.0 | 245 | 0.9397 | 0.5529 |
| 0.6921 | 8.0 | 280 | 0.9680 | 0.5647 |
| 0.684 | 9.0 | 315 | 0.9681 | 0.5647 |
| 0.6558 | 10.0 | 350 | 0.9634 | 0.5765 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu129
- Datasets 4.2.0
- Tokenizers 0.22.1
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Model tree for hawalurahman/xlm-roberta-base-difficulty-prediction
Base model
FacebookAI/xlm-roberta-base