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---
base_model: BramVanroy/GEITje-7B-ultra
datasets:
- BramVanroy/ultra_feedback_dutch
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: FinGEITje-7B-dpo
results: []
language:
- nl
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/snoels/huggingface/runs/yng7mdb0)
# FinGEITje-7B-dpo
This model is a fine-tuned version of [/mnt/trained_models/fingeitje](https://huggingface.co//mnt/trained_models/fingeitje) on the BramVanroy/ultra_feedback_dutch dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0279
- Rewards/chosen: -3.8986
- Rewards/rejected: -15.9713
- Rewards/accuracies: 0.9836
- Rewards/margins: 12.0727
- Logps/rejected: -1952.6360
- Logps/chosen: -789.0983
- Logits/rejected: -1.7369
- Logits/chosen: -1.8936
## 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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1029 | 0.1327 | 100 | 0.1099 | -1.8067 | -5.3683 | 0.9679 | 3.5616 | -892.3373 | -579.9115 | -2.4775 | -2.3705 |
| 0.042 | 0.2654 | 200 | 0.0430 | -3.5129 | -10.6778 | 0.9828 | 7.1649 | -1423.2883 | -750.5289 | -1.9744 | -1.9895 |
| 0.0278 | 0.3981 | 300 | 0.0344 | -3.7335 | -13.5153 | 0.9828 | 9.7818 | -1707.0360 | -772.5893 | -1.7454 | -1.8191 |
| 0.0223 | 0.5308 | 400 | 0.0308 | -3.6554 | -13.7712 | 0.9858 | 10.1158 | -1732.6289 | -764.7831 | -1.8020 | -1.9184 |
| 0.0378 | 0.6635 | 500 | 0.0297 | -4.0018 | -16.3285 | 0.9851 | 12.3266 | -1988.3542 | -799.4221 | -1.6924 | -1.8650 |
| 0.0352 | 0.7962 | 600 | 0.0278 | -3.8104 | -15.6430 | 0.9836 | 11.8327 | -1919.8119 | -780.2752 | -1.7437 | -1.8978 |
| 0.0238 | 0.9289 | 700 | 0.0279 | -3.8974 | -15.9642 | 0.9828 | 12.0668 | -1951.9310 | -788.9780 | -1.7371 | -1.8937 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1 |