--- base_model: meta-llama/Llama-3.2-1B datasets: - prachathai67k library_name: peft license: llama3.2 metrics: - accuracy - f1 - precision - recall tags: - generated_from_trainer model-index: - name: nlp-prachathai67k-text-classification results: [] --- # nlp-prachathai67k-text-classification This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the prachathai67k dataset. It achieves the following results on the evaluation set: - Loss: 0.1609 - Accuracy: 0.9349 - F1: 0.7418 - Precision: 0.8033 - Recall: 0.6890 ## 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: 3 - eval_batch_size: 3 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 12 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.1687 | 0.9998 | 4531 | 0.1698 | 0.9302 | 0.7251 | 0.7787 | 0.6784 | | 0.1513 | 1.9997 | 9062 | 0.1609 | 0.9349 | 0.7418 | 0.8033 | 0.6890 | ### Framework versions - PEFT 0.13.0 - Transformers 4.44.2 - Pytorch 2.4.0 - Datasets 3.0.0 - Tokenizers 0.19.1