af4662d21a
Model: open-sci/sft__ot30k_Qwen3-1.7B-Base-DPO-Tulu3-decontaminated Source: Original Platform
library_name, license, base_model, tags, datasets, model-index
| library_name | license | base_model | tags | datasets | model-index | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | other | ali-elganzory/Qwen3-1.7B-Base-DPO-Tulu3-decontaminated |
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sft__f679a5c592c8dffb__e84ac435ea2b3dc4d1f4__qwen3-steps
This model is a fine-tuned version of ali-elganzory/Qwen3-1.7B-Base-DPO-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.
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: 4
- total_train_batch_size: 128
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5.0
Training results
Framework versions
- Transformers 5.5.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2