laion/sera-316-opt1k__Qwen3-8B
The laion/sera-316-opt1k__Qwen3-8B model is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. It was trained on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--allenai-sera-unified-316/snapshots/ef551d7ec9bb11780e15657490451a6fc6842c46_thinking_preprocessed dataset. This model is optimized for tasks related to the specific dataset it was fine-tuned on, offering specialized performance for its intended domain.
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Model Overview
laion/sera-316-opt1k__Qwen3-8B is an 8 billion parameter language model, fine-tuned from the base Qwen/Qwen3-8B architecture. This model was specifically trained on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--allenai-sera-unified-316/snapshots/ef551d7ec9bb11780e15657490451a6fc6842c46_thinking_preprocessed dataset.
Training Details
The fine-tuning process utilized the following key hyperparameters:
- Learning Rate: 4e-05
- Batch Size: 1 (train), 8 (eval)
- Gradient Accumulation Steps: 3, leading to a total effective training batch size of 96
- Optimizer: AdamW_Torch_Fused with betas=(0.85, 0.98) and epsilon=1e-08
- LR Scheduler: Cosine type with a warmup ratio of 0.1
- Epochs: 7.0
- Distributed Training: Multi-GPU setup across 32 devices.
Intended Use
While specific intended uses and limitations are not detailed in the provided information, the model's fine-tuning on a particular dataset suggests its primary utility lies in applications aligned with the characteristics and content of that dataset. Developers should consider the nature of the allenai-sera-unified-316 dataset when evaluating its suitability for their specific use cases.