laion/swesmith-1000-opt1k__Qwen3-8B
The laion/swesmith-1000-opt1k__Qwen3-8B is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B. This model was trained on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--swesmith-unified-1000/snapshots/031ef1b66d8d55421f68d0afcbf7872ef3644c1e_thinking_preprocessed dataset. It leverages a 32768 token context length and is designed for general language generation tasks based on its Qwen3 architecture.
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Model Overview
The laion/swesmith-1000-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 laion/swesmith-unified-1000 dataset, indicating a potential specialization or adaptation to the characteristics of this particular data.
Training Details
The fine-tuning process involved several key hyperparameters:
- Learning Rate: 4e-05
- Batch Size: A
train_batch_sizeof 1 withgradient_accumulation_stepsof 3, resulting in atotal_train_batch_sizeof 96. - Optimizer: Utilized
ADAMW_TORCH_FUSEDwith specific beta values and epsilon. - Scheduler: A cosine learning rate scheduler with a 0.1 warmup ratio.
- Epochs: Trained for 7.0 epochs across 32 devices.
Intended Use
While specific intended uses and limitations require further information, as a fine-tuned Qwen3-8B model, it is generally suitable for a broad range of natural language processing tasks, including text generation, summarization, and question answering, particularly benefiting from its 32768 token context length. Its performance characteristics would be influenced by the specific nature of the swesmith-unified-1000 dataset.