sera-3160__Qwen3-8B

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sera-3160__Qwen3-8B

This model is a fine-tuned version of Qwen/Qwen3-8B on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--allenai-sera-unified-3160/snapshots/099497cdf98a9c3da57ca8873d9d734da4be1361_thinking_preprocessed dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 4e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 32
• gradient_accumulation_steps: 3
• total_train_batch_size: 96
• total_eval_batch_size: 256
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 7.0

Training results

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.1+cu130
• Datasets 4.7.0
• Tokenizers 0.22.2