laion/swesmith-316-opt1k__Qwen3-8B
The laion/swesmith-316-opt1k__Qwen3-8B is an 8 billion parameter causal 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-316/snapshots/2990d3acbbe8e6622cfe408e0f12038e523310ec_thinking_preprocessed dataset, suggesting a specialization in processing or generating content related to the dataset's characteristics. With a 32768 token context length, it is suitable for tasks requiring extensive contextual understanding.
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Overview
This model, laion/swesmith-316-opt1k__Qwen3-8B, is an 8 billion parameter language model derived from the Qwen3-8B architecture. It has undergone fine-tuning on a specific dataset, /e/data1/datasets/playground/ot/hf_hub/datasets--laion--swesmith-unified-316/snapshots/2990d3acbbe8e6622cfe408e0f12038e523310ec_thinking_preprocessed, indicating a potential specialization in areas covered by this training data. The model supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The fine-tuning process utilized the following key hyperparameters:
- Learning Rate: 4e-05
- Batch Sizes:
train_batch_sizeof 1,eval_batch_sizeof 8, with agradient_accumulation_stepsof 3, leading to atotal_train_batch_sizeof 96. - Optimizer: ADAMW_TORCH_FUSED with specific beta and epsilon values.
- Scheduler: Cosine learning rate scheduler with a 0.1 warmup ratio.
- Epochs: Trained for 7.0 epochs.
Intended Uses & Limitations
Specific intended uses and limitations are not detailed in the provided model card. Users should evaluate its performance on their specific tasks, especially considering the unique fine-tuning dataset. The model's large context window makes it suitable for applications requiring extensive input or output generation.