Instructions to use KABANDA18/FineTuning-Roberta-base_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KABANDA18/FineTuning-Roberta-base_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KABANDA18/FineTuning-Roberta-base_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KABANDA18/FineTuning-Roberta-base_Model") model = AutoModelForSequenceClassification.from_pretrained("KABANDA18/FineTuning-Roberta-base_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
FineTuning-Roberta-base_Model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3400
- Accuracy: 0.7945
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6351 | 0.2 | 100 | 0.5536 | 0.587 |
| 0.4783 | 0.4 | 200 | 0.4386 | 0.7145 |
| 0.4252 | 0.6 | 300 | 0.4041 | 0.723 |
| 0.4068 | 0.8 | 400 | 0.3815 | 0.7415 |
| 0.3978 | 1.0 | 500 | 0.3811 | 0.7265 |
| 0.3837 | 1.2 | 600 | 0.3717 | 0.7645 |
| 0.35 | 1.4 | 700 | 0.3816 | 0.7545 |
| 0.3575 | 1.6 | 800 | 0.3403 | 0.7755 |
| 0.3437 | 1.8 | 900 | 0.3431 | 0.7805 |
| 0.3172 | 2.0 | 1000 | 0.3346 | 0.793 |
| 0.2722 | 2.2 | 1100 | 0.3535 | 0.7835 |
| 0.2792 | 2.4 | 1200 | 0.3411 | 0.7865 |
| 0.2668 | 2.6 | 1300 | 0.3328 | 0.793 |
| 0.2701 | 2.8 | 1400 | 0.3379 | 0.794 |
| 0.2651 | 3.0 | 1500 | 0.3400 | 0.7945 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for KABANDA18/FineTuning-Roberta-base_Model
Base model
FacebookAI/roberta-base