--- library_name: transformers license: llama3.1 base_model: meta-llama/Llama-3.1-8B tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - generated_from_trainer datasets: - oxford-llms/ultrachat_filtered - oxford-llms/Magpie-Qwen2.5-Pro-1M-v0.1-filtered - oxford-llms/european_social_survey_2020_sft - oxford-llms/european_social_survey_2023_sft - oxford-llms/world_values_survey_2017_2022_sft model-index: - name: llama3-1-ox-llms-8b-sft-full-3-epochs results: [] --- # llama3-1-ox-llms-8b-sft-full-3-epochs This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the oxford-llms/ultrachat_filtered, the oxford-llms/Magpie-Qwen2.5-Pro-1M-v0.1-filtered, the oxford-llms/european_social_survey_2020_sft, the oxford-llms/european_social_survey_2023_sft and the oxford-llms/world_values_survey_2017_2022_sft datasets. It achieves the following results on the evaluation set: - Loss: 0.8089 ## 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: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - total_train_batch_size: 64 - total_eval_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.6884 | 1.0 | 1924 | 0.7764 | | 0.5899 | 2.0 | 3848 | 0.7568 | | 0.4984 | 3.0 | 5772 | 0.8089 | ### Framework versions - Transformers 4.45.1 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.20.3