RaulJimenezS/qwen3-05b-full-test
RaulJimenezS/qwen3-05b-full-test is a 0.5 billion parameter causal language model, fine-tuned from Qwen/Qwen2.5-0.5B-Instruct. This model was trained for 1 epoch with a learning rate of 2e-05 and a context length of 32768 tokens. It is a test model, primarily demonstrating a fine-tuning process rather than optimized for a specific application.
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Model Overview
This model, RaulJimenezS/qwen3-05b-full-test, is a fine-tuned version of the Qwen/Qwen2.5-0.5B-Instruct base model. It features approximately 0.5 billion parameters and supports a context length of 32768 tokens. The primary purpose of this model appears to be for testing fine-tuning procedures, as indicated by its name and the limited information provided in its description.
Training Details
The model underwent a single epoch of training with a learning rate of 2e-05. Key training hyperparameters include a train_batch_size of 1, gradient_accumulation_steps of 8, and an AdamW optimizer. The training process resulted in a loss of 1.1966 on the evaluation set.
Intended Use
Given the limited information, this model is best suited for:
- Experimentation with fine-tuning: Developers can use this as an example of a fine-tuned Qwen 2.5-0.5B variant.
- Understanding training parameters: The provided hyperparameters offer insight into a specific fine-tuning setup.
Further details regarding specific capabilities, limitations, and intended uses are not explicitly provided in the model card.