--- base_model: meta-llama/Meta-Llama-3.1-8B datasets: - llama-duo/synth_classification_dataset_dedup library_name: peft license: llama3.1 tags: - alignment-handbook - trl - sft - generated_from_trainer model-index: - name: llama3.1-8b-classification-gpt4o-100k results: [] --- # llama3.1-8b-classification-gpt4o-100k This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the llama-duo/synth_classification_dataset_dedup dataset. It achieves the following results on the evaluation set: - Loss: 3.0330 ## 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: 4 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 8 - 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 | |:-------------:|:-----:|:----:|:---------------:| | 1.2062 | 1.0 | 296 | 1.6781 | | 1.1339 | 2.0 | 592 | 1.6897 | | 1.0779 | 3.0 | 888 | 1.7536 | | 1.0043 | 4.0 | 1184 | 1.8225 | | 0.9288 | 5.0 | 1480 | 2.0044 | | 0.8437 | 6.0 | 1776 | 2.1710 | | 0.7654 | 7.0 | 2072 | 2.4080 | | 0.7117 | 8.0 | 2368 | 2.6554 | | 0.6916 | 9.0 | 2664 | 2.9172 | | 0.6652 | 10.0 | 2960 | 3.0330 | ### Framework versions - PEFT 0.12.0 - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1