This model is a fine-tuned version of
secmlr/DS-Noisy_DS-Clean_DS-OSS_QWQ-OSS_QWQ-Clean_QWQ-Noisy_Con_Qwen2.5-7B-Instruct_sft
on the ruizhe_simplier_reasoning_ds_clean_32k, the ruizhe_simplier_reasoning_ds_noisy_32k, the ruizhe_simplier_reasoning_ds_ossfuzz_32k, the ruizhe_simplier_reasoning_qwq_clean_32k, the ruizhe_simplier_reasoning_qwq_noisy_small_32k and the ruizhe_simplier_reasoning_qwq_ossfuzz_32k datasets.
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: 1e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 12
total_train_batch_size: 24
total_eval_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
Runs of secmlr final_model on huggingface.co
3
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
-9
30-day runs
More Information About final_model huggingface.co Model
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