Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) facebook-opt-350m-asoria-love-poems - AWQ - Model creator: https://huggingface.co/asoria/ - Original model: https://huggingface.co/asoria/facebook-opt-350m-asoria-love-poems/ Original model description: --- library_name: transformers license: other base_model: facebook/opt-350m tags: - trl - sft - generated_from_trainer model-index: - name: facebook-opt-350m-asoria-love-poems results: [] --- # facebook-opt-350m-asoria-love-poems This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.9815 - Model Preparation Time: 0.005 ## 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: 0.0002 - train_batch_size: 1 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 100 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1