--- base_model: HuggingFaceTB/SmolLM-1.7B-Instruct library_name: peft license: apache-2.0 tags: - trl - sft - generated_from_trainer model-index: - name: SmolLM-1.7B-Instruct-Summarization-Adapter_r16_alpha16_lr5e-4_rsloratrue results: [] --- # SmolLM-1.7B-Instruct-Summarization-Adapter_r16_alpha16_lr5e-4_rsloratrue This model is a fine-tuned version of [HuggingFaceTB/SmolLM-1.7B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-1.7B-Instruct) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.7641 ## 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: 0.0005 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.7391 | 1.0 | 1266 | 1.7641 | ### Framework versions - PEFT 0.13.2 - Transformers 4.45.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1