64 lines
1.6 KiB
Markdown
64 lines
1.6 KiB
Markdown
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---
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library_name: transformers
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license: other
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base_model: ali-elganzory/Qwen3-1.7B-Base-SFT-Tulu3-decontaminated
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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datasets:
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- arrow
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model-index:
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- name: sft__f679a5c592c8dffb__b4bfd93d8848cb99e95a__qwen3-steps
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# sft__f679a5c592c8dffb__b4bfd93d8848cb99e95a__qwen3-steps
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This model is a fine-tuned version of [ali-elganzory/Qwen3-1.7B-Base-SFT-Tulu3-decontaminated](https://huggingface.co/ali-elganzory/Qwen3-1.7B-Base-SFT-Tulu3-decontaminated) on the /gpfs/scratch/ehpc524/ot/hf_hub/datasets/open-thoughts_open_thoughts3-1.2_m_30000_samples/default/0.0.0/f679a5c592c8dffb dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4e-05
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 32
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 256
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 0.1
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- num_epochs: 5.0
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### Training results
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### Framework versions
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- Transformers 5.5.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.8.4
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- Tokenizers 0.22.2
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