Edit model card

Weni/WeniGPT-2.5.3-Zephyr-7B-zephyr-prompt-LLM_Base_2.0.3_DPO_reduction_variation

This model is a fine-tuned version of [Weni/WeniGPT-2.2.3-Zephyr-7B-merged-LLM_Base_2.0.3_SFT] on the dataset Weni/LLM_Base_2.0.3_DPO with the DPO trainer. It is part of the DPO project for Weni.

It achieves the following results on the evaluation set: {'eval_loss': 0.6931472420692444, 'eval_runtime': 173.8803, 'eval_samples_per_second': 2.824, 'eval_steps_per_second': 1.415, 'eval_rewards/chosen': 0.0, 'eval_rewards/rejected': 0.0, 'eval_rewards/accuracies': 0.0, 'eval_rewards/margins': 0.0, 'eval_logps/rejected': -204.64605712890625, 'eval_logps/chosen': -64.2483901977539, 'eval_logits/rejected': -2.031214475631714, 'eval_logits/chosen': -1.649370789527893, 'epoch': 0.0}

Intended uses & limitations

This model has not been trained to avoid specific intructions.

Training procedure

Finetuning was done on the model Weni/WeniGPT-2.2.3-Zephyr-7B-merged-LLM_Base_2.0.3_SFT with the following prompt:

Question:
<|user|>{question}</s>


Chosen:
<|assistant|>{correct_ans}</s>


Rejected:
<|assistant|>{rejected_ans}</s>

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • per_device_train_batch_size: 8
  • per_device_eval_batch_size: 2
  • gradient_accumulation_steps: 2
  • num_gpus: 1
  • total_train_batch_size: 16
  • optimizer: AdamW
  • lr_scheduler_type: cosine
  • num_steps: 1
  • quantization_type: bitsandbytes
  • LoRA: ("\n - bits: 4\n - use_exllama: True\n - device_map: auto\n - use_cache: False\n - lora_r: 8\n - lora_alpha: 16\n - lora_dropout: 0.1\n - bias: none\n - target_modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj']\n - task_type: CAUSAL_LM",)

Training results

Framework versions

Hardware

  • Cloud provided: runpod.io
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for Weni/WeniGPT-2.5.3-Zephyr-7B-zephyr-prompt-LLM_Base_2.0.3_DPO_reduction_variation