Wisenut-3.1-70B-Instruct-4Bit-Lora-DPO
This model is a fine-tuned version of NousResearch/Meta-Llama-3.1-70B-Instruct on the dpo_v1_normal_10000 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-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 1.0
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.43.4
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for wisenut-nlp-team/Wisenut-LLaMA-3.1-70B-Instruct-4Bit-Lora-DPO
Base model
NousResearch/Meta-Llama-3.1-70B-Instruct