--- base_model: meta-llama/Meta-Llama-3-8B datasets: - llama-duo/synth_closed_qa_dataset_dedup library_name: peft license: llama3 tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: llama3.1-8b-closedqa-gpt4o-100k results: [] --- # llama3.1-8b-closedqa-gpt4o-100k This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the llama-duo/synth_closed_qa_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 2.1008 ## 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: 8 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.8026 | 1.0 | 256 | 2.0456 | | 0.7532 | 2.0 | 512 | 2.0313 | | 0.7198 | 3.0 | 768 | 2.0404 | | 0.7053 | 4.0 | 1024 | 2.0419 | | 0.6831 | 5.0 | 1280 | 2.0541 | | 0.6633 | 6.0 | 1536 | 2.0744 | | 0.6595 | 7.0 | 1792 | 2.0814 | | 0.6374 | 8.0 | 2048 | 2.0939 | | 0.6277 | 9.0 | 2304 | 2.0994 | | 0.616 | 10.0 | 2560 | 2.1008 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1