Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mjaydenkim/roberta-finetuned-inspirational with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjaydenkim/roberta-finetuned-inspirational with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mjaydenkim/roberta-finetuned-inspirational")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjaydenkim/roberta-finetuned-inspirational") model = AutoModelForSequenceClassification.from_pretrained("mjaydenkim/roberta-finetuned-inspirational") - Notebooks
- Google Colab
- Kaggle
roberta-finetuned-inspirational
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: 0.2116
- F1: 0.9398
- Roc Auc: 0.9398
- Accuracy: 0.8394
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3126 | 1.0 | 621 | 0.1732 | 0.9266 | 0.9267 | 0.7905 |
| 0.177 | 2.0 | 1242 | 0.1861 | 0.9229 | 0.9230 | 0.7865 |
| 0.127 | 3.0 | 1863 | 0.2499 | 0.9228 | 0.9228 | 0.7915 |
| 0.0906 | 4.0 | 2484 | 0.2306 | 0.9355 | 0.9355 | 0.8228 |
| 0.045 | 5.0 | 3105 | 0.2444 | 0.9332 | 0.9332 | 0.8197 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.0+xpu
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for mjaydenkim/roberta-finetuned-inspirational
Base model
FacebookAI/xlm-roberta-base