laion/sera-316__Qwen3-8B
The laion/sera-316__Qwen3-8B is an 8 billion parameter language model fine-tuned from the Qwen/Qwen3-8B architecture. This model was specifically trained on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--allenai-sera-unified-316 dataset. It leverages a 32768 token context length, making it suitable for tasks requiring extensive contextual understanding. The fine-tuning process aimed to adapt the base Qwen3-8B model for specific applications related to the SERA unified dataset.
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Model Overview
The laion/sera-316__Qwen3-8B is an 8 billion parameter language model, building upon the robust Qwen/Qwen3-8B architecture. This model has undergone a specific fine-tuning process using the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--allenai-sera-unified-316 dataset. It supports a substantial context length of 32768 tokens, enabling it to process and generate longer sequences of text.
Training Details
The fine-tuning was conducted with the following key hyperparameters:
- Learning Rate: 4e-05
- Batch Size: 1 (train), 8 (eval)
- Gradient Accumulation: 3 steps, leading to a total effective training batch size of 96
- Optimizer: AdamW_Torch_Fused with betas=(0.9, 0.98) and epsilon=1e-08
- Epochs: 7.0
- Scheduler: Cosine learning rate scheduler with a 0.1 warmup ratio
This specialized training on the allenai-sera-unified-316 dataset suggests its potential utility in applications aligned with the characteristics and content of that specific data source. Further details on intended uses and limitations would require more information about the dataset's nature.