Instructions to use swarajjena/xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swarajjena/xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="swarajjena/xlm-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("swarajjena/xlm-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("swarajjena/xlm-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
xlm-roberta-base
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: 0.8000
- Accuracy: 0.6992
- F1 Score: 0.7180
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-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch 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 | F1 Score |
|---|---|---|---|---|---|
| 1.1311 | 1.0 | 1214 | 0.8135 | 0.6881 | 0.7065 |
| 1.0277 | 2.0 | 2428 | 0.7818 | 0.6922 | 0.7094 |
| 0.9452 | 3.0 | 3642 | 0.7964 | 0.6889 | 0.7073 |
| 0.8883 | 4.0 | 4856 | 0.7437 | 0.7176 | 0.7283 |
| 0.8358 | 5.0 | 6070 | 0.7759 | 0.7071 | 0.7221 |
| 0.7933 | 6.0 | 7284 | 0.8005 | 0.6871 | 0.7102 |
| 0.76 | 7.0 | 8498 | 0.8228 | 0.6846 | 0.7072 |
| 0.7409 | 8.0 | 9712 | 0.7787 | 0.7066 | 0.7228 |
| 0.7068 | 9.0 | 10926 | 0.8122 | 0.6931 | 0.7148 |
| 0.6922 | 10.0 | 12140 | 0.8000 | 0.6992 | 0.7180 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3
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Model tree for swarajjena/xlm-roberta-base
Base model
FacebookAI/xlm-roberta-base