gyanbhambhani/oss-jev-qwen05-decision
The gyanbhambhani/oss-jev-qwen05-decision model is a 0.5 billion parameter language model fine-tuned from Qwen/Qwen2.5-0.5B-Instruct. It was trained for 2000 steps with a learning rate of 2e-05 and achieved a validation loss of 0.4809. The primary use case and specific differentiators are not detailed in the provided information.
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Overview
The gyanbhambhani/oss-jev-qwen05-decision model is a fine-tuned variant of the Qwen2.5-0.5B-Instruct base model, developed by Qwen. This model has 0.5 billion parameters and was trained for 2000 steps. While the specific dataset used for fine-tuning is not disclosed, the training process resulted in a validation loss of 0.4809.
Key Training Details
- Base Model: Qwen/Qwen2.5-0.5B-Instruct
- Learning Rate: 2e-05
- Optimizer: ADAMW_TORCH_FUSED
- Training Steps: 2000
- Validation Loss: 0.4809
Good for
- Further experimentation or fine-tuning on specific tasks where a small, efficient model is required.
- Use cases that benefit from the Qwen2.5 architecture in a compact form factor.
Further details regarding intended uses, limitations, and the specific training data are not available in the current model card.