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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-0.5B |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- generated_from_trainer |
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- instruction-tuning |
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model-index: |
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- name: outputs/qwen2.5-0.5b-ft-synthia15-i |
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results: [] |
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--- |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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# Qwen2.5-0.5B Fine-tuned on Synthia v1.5-I |
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This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the Synthia v1.5-I dataset, which contains over 20.7k instruction-following examples. |
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## Model Description |
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Qwen2.5-0.5B is part of the latest Qwen2.5 series of large language models. The base model brings significant improvements in: |
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- Instruction following and generating long texts |
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- Understanding structured data and generating structured outputs |
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- Support for over 29 languages |
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- Long context support up to 32,768 tokens |
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This fine-tuned version enhances the base model's instruction-following capabilities through training on the Synthia v1.5-I dataset. |
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### Model Architecture |
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- Type: Causal Language Model |
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- Parameters: 0.49B (0.36B non-embedding) |
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- Layers: 24 |
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- Attention Heads: 14 for Q and 2 for KV (GQA) |
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- Context Length: 32,768 tokens |
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- Training Framework: Transformers 4.45.0.dev0 |
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## Intended Uses & Limitations |
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This model is intended for: |
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- Instruction following and task completion |
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- Text generation and completion |
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- Conversational AI applications |
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The model inherits the multilingual capabilities and long context support of the base Qwen2.5-0.5B model, while being specifically tuned for instruction following. |
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## Training Procedure |
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### Training Data |
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The model was fine-tuned on the Synthia v1.5-I dataset containing 20.7k instruction-following examples. |
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### Training Hyperparameters |
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The following hyperparameters were used during training: |
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- Learning rate: 1e-05 |
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- Train batch size: 5 |
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- Eval batch size: 5 |
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- Seed: 42 |
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- Gradient accumulation steps: 8 |
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- Total train batch size: 40 |
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- Optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- LR scheduler type: cosine |
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- LR scheduler warmup steps: 100 |
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- Number of epochs: 3 |
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- Sequence length: 4096 |
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- Sample packing: enabled |
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- Pad to sequence length: enabled |
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## Framework Versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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