README.md

metadata

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
  - oxford-llms/european_social_survey_2023_germany_sft
model-index:
  - name: llama3-1-ox-llms-8b-sft-full-germany-data
    results: []

llama3-1-ox-llms-8b-sft-full-germany-data

This model is a fine-tuned version of 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, the oxford-llms/world_values_survey_2017_2022_sft and the oxford-llms/european_social_survey_2023_germany_sft datasets. It achieves the following results on the evaluation set:

• Loss: 0.7417

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.6603	1.0	2100	0.7572
0.56	2.0	4200	0.7417

Framework versions

• Transformers 4.45.1
• Pytorch 2.5.1+cu124
• Datasets 3.1.0
• Tokenizers 0.20.3