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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama3-1-ox-llms-8b-sft-full-germany-data
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, 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