--- license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T tags: - generated_from_trainer model-index: - name: Context aware splitter 1.1b results: [] datasets: - mhenrichsen/context-aware-splits-english language: - en --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) # Context aware splitter 1.1b This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0598 ## Model description - This model is used to split texts in a context aware way. Used for RAG applications. - This model is based off TinyLLaMA 1.1b It uses the Alpaca format: ``` Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Your task is to segment text into smaller blocks. Split the text where it makes sense and be vary of the context. The ideal split should be close to {WORD_COUNT} words. ### Input: Q: Information/File Manager I'm looking for a file manager application which helps to organize a large amount of movies, pictures, music, text documents, databases, audio-books and ebooks. Right now I only use the Finder which doesn't work well, because I really need a function to put single files into multiple categories. Simply using the file system for this creates a confusing nesting of files. A: Depending on the number of categories you require to handle, you could always use a combination of the finder with the built in label functionality, thus a movie can be held in one area (movies directory, for example), but "tagged" as something else. Using smart directories and saved searches you can view your files by a combination of the attributes (location, label, media type) to create custom views. All without purchasing software. Cheap and cheerful, but may be suitable to your needs. A: Maybe use a file manager that supports Open Meta. Or use symbolic links for organizing all your media files. Or even use hardlinked files if you dare. ### Response: ``` Response: ``` {'splits': ["Q: Information/File Manager I'm looking for a file manager application which helps to organize a large amount of movies, pictures, music, text documents, databases, audio-books and ebooks. Right now I only use the Finder which doesn't work well, because I really need a function to put single files into multiple categories. Simply using the file system for this creates a confusing nesting of files.", 'A: Depending on the number of categories you require to handle, you could always use a combination of the finder with the built in label functionality, thus a movie can be held in one area (movies directory, for example), but "tagged" as something else. Using smart directories and saved searches you can view your files by a combination of the attributes (location, label, media type) to create custom views. All without purchasing software. Cheap and cheerful, but may be suitable to your needs.', 'A: Maybe use a file manager that supports Open Meta. Or use symbolic links for organizing all your media files. Or even use hardlinked files if you dare.'], 'topic': 'Discussion on file manager applications for organizing large amount of media files.'} ``` ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.9849 | 0.03 | 1 | 2.0811 | | 1.3107 | 0.17 | 5 | 1.1992 | | 0.6399 | 0.34 | 10 | 0.6359 | | 0.2779 | 0.51 | 15 | 0.2862 | | 0.1807 | 0.68 | 20 | 0.1634 | | 0.1256 | 0.85 | 25 | 0.1177 | | 0.097 | 1.0 | 30 | 0.0891 | | 0.1063 | 1.17 | 35 | 0.0734 | | 0.0769 | 1.34 | 40 | 0.0723 | | 0.0694 | 1.51 | 45 | 0.0633 | | 0.0687 | 1.69 | 50 | 0.0624 | | 0.0575 | 1.86 | 55 | 0.0622 | | 0.0516 | 2.01 | 60 | 0.0609 | | 0.0582 | 2.18 | 65 | 0.0603 | | 0.0611 | 2.35 | 70 | 0.0600 | | 0.0515 | 2.52 | 75 | 0.0598 | | 0.0704 | 2.69 | 80 | 0.0598 | | 0.0525 | 2.86 | 85 | 0.0598 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.0.1+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0