Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) opt-350m-finetuned-slangQA - AWQ - Model creator: https://huggingface.co/vrvenkatesh/ - Original model: https://huggingface.co/vrvenkatesh/opt-350m-finetuned-slangQA/ Original model description: --- license: other base_model: facebook/opt-350m tags: - generated_from_trainer model-index: - name: opt-350m-finetuned-slangQA results: [] --- # opt-350m-finetuned-slangQA This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0236 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 3.2105 | 1.0 | 1020 | 3.1122 | | 2.7784 | 2.0 | 2040 | 3.0349 | | 2.5066 | 3.0 | 3060 | 3.0236 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0