dpo_finetuned
This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-0528-Qwen3-8B on the custom_dpo 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: 5e-06
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 1
Training results
Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for tanish45678/DeepSeek-R1-0528-Qwen3-8B
Base model
deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-R1-0528-Qwen3-8B") model = PeftModel.from_pretrained(base_model, "tanish45678/DeepSeek-R1-0528-Qwen3-8B")