--- library_name: transformers license: llama3.1 base_model: mlfoundations-dev/stackexchange_christianity tags: - llama-factory - full - trl - dpo - llama-factory - generated_from_trainer model-index: - name: simpo-stackexchange_christianity results: [] --- # simpo-stackexchange_christianity This model is a fine-tuned version of [mlfoundations-dev/stackexchange_christianity](https://huggingface.co/mlfoundations-dev/stackexchange_christianity) on the mlfoundations-dev/gemma2-ultrafeedback-armorm dataset. It achieves the following results on the evaluation set: - Loss: 2.5820 - Rewards/chosen: -43.5673 - Rewards/rejected: -50.3578 - Rewards/accuracies: 0.7914 - Rewards/margins: 6.7905 - Logps/chosen: -4.3567 - Logps/rejected: -5.0358 - Logits/chosen: -0.9251 - Logits/rejected: -0.9405 ## 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: 8e-07 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - total_eval_batch_size: 16 - 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: 1.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:| | 2.7111 | 0.9997 | 442 | 2.5820 | -43.5673 | -50.3578 | 0.7914 | 6.7905 | -4.3567 | -5.0358 | -0.9251 | -0.9405 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.3.0 - Datasets 3.1.0 - Tokenizers 0.20.3