Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) my-szw-model - bnb 4bits - Model creator: https://huggingface.co/marc4gov/ - Original model: https://huggingface.co/marc4gov/my-szw-model/ Original model description: --- library_name: transformers license: mit base_model: BramVanroy/fietje-2-instruct tags: - generated_from_trainer model-index: - name: my-szw-model results: [] --- # my-szw-model This model is a fine-tuned version of [BramVanroy/fietje-2-instruct](https://huggingface.co/BramVanroy/fietje-2-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3317 ## 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: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 67 | 1.1677 | | No log | 2.0 | 134 | 1.2020 | | No log | 3.0 | 201 | 1.3317 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1 - Datasets 3.1.0 - Tokenizers 0.20.3