Instructions to use Georgios-Ak/Website_Fine_Tuned_Classification_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Georgios-Ak/Website_Fine_Tuned_Classification_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Georgios-Ak/Website_Fine_Tuned_Classification_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Georgios-Ak/Website_Fine_Tuned_Classification_Model") model = AutoModelForSequenceClassification.from_pretrained("Georgios-Ak/Website_Fine_Tuned_Classification_Model") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| license: llama3.2 | |
| base_model: meta-llama/Llama-3.2-1B-Instruct | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: Website_Fine_Tuned_Classification_Model | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # classification_fine_tuning_results | |
| This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0140 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:------:|:----:|:---------------:| | |
| | No log | 1.0 | 53 | 0.0061 | | |
| | No log | 2.0 | 106 | 0.0086 | | |
| | No log | 3.0 | 159 | 0.0103 | | |
| | No log | 4.0 | 212 | 0.0098 | | |
| | No log | 4.9143 | 260 | 0.0096 | | |
| ### Framework versions | |
| - Transformers 4.48.0 | |
| - Pytorch 2.5.1+cu118 | |
| - Datasets 3.2.0 | |
| - Tokenizers 0.21.0 | |