dpo
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the dpo-anubis 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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: 35.0
Training results
Framework versions
- PEFT 0.11.1
- Transformers 4.48.3
- Pytorch 2.4.0
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for danushkhanna/Llama-3.1-8B-Instruct-anubis_dpo
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct