llama3-8b-instruct-wo-kqa_golden-iter-dpo-step1
This model is a fine-tuned version of Minbyul/llama3-8b-instruct-wo-kqa_golden-iter-sft-step1 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6931
- Rewards/chosen: 0.0
- Rewards/rejected: 0.0
- Rewards/accuracies: 0.0
- Rewards/margins: 0.0
- Logps/rejected: -369.7173
- Logps/chosen: -476.8867
- Logits/rejected: -0.5081
- Logits/chosen: -0.6523
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-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
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