Harshvardhan95555/qwen3-finetuned
Harshvardhan95555/qwen3-finetuned is a 0.8 billion parameter language model, fine-tuned from Qwen/Qwen3-0.6B. This model was trained for 1 epoch with a learning rate of 2e-05 and achieved a validation loss of 3.1459. Due to limited information on its training dataset and intended uses, its specific differentiators and optimal applications are not clearly defined.
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Model Overview
This model, Harshvardhan95555/qwen3-finetuned, is a fine-tuned variant of the Qwen3-0.6B architecture. It features approximately 0.8 billion parameters and was trained for a single epoch. The training process utilized a learning rate of 2e-05 with an AdamW optimizer, achieving a validation loss of 3.1459.
Key Training Details
- Base Model: Qwen/Qwen3-0.6B
- Parameters: ~0.8 billion
- Learning Rate: 2e-05
- Optimizer: AdamW_TORCH_FUSED
- Epochs: 1
- Validation Loss: 3.1459
- Frameworks: Transformers 5.13.1, Pytorch 2.11.0+cu128, Datasets 4.0.0, Tokenizers 0.22.2
Limitations and Information Gaps
Currently, the specific dataset used for fine-tuning is unknown, and detailed information regarding the model's intended uses, limitations, and the nature of its training and evaluation data is not provided in the available documentation. This limits the ability to identify its unique strengths or optimal use cases compared to other models.