--- library_name: transformers license: llama3.1 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct tags: - alignment-handbook - generated_from_trainer datasets: - simonycl/llama3.1-ultrafeedback-annotate-armorm model-index: - name: llama-3.1-8b-instruct-armorm results: [] --- # llama-3.1-8b-instruct-armorm This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the simonycl/llama3.1-ultrafeedback-annotate-armorm dataset. It achieves the following results on the evaluation set: - Loss: 0.3837 - Rewards/chosen: -3.2511 - Rewards/rejected: -5.1202 - Rewards/accuracies: 0.8644 - Rewards/margins: 1.8691 - Logps/rejected: -797.6878 - Logps/chosen: -602.0981 - Logits/rejected: -1.3603 - Logits/chosen: -1.3921 ## 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: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 32 - total_train_batch_size: 128 - total_eval_batch_size: 4 - 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 | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.4269 | 0.8444 | 400 | 0.3837 | -3.2511 | -5.1202 | 0.8644 | 1.8691 | -797.6878 | -602.0981 | -1.3603 | -1.3921 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1