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---
library_name: peft
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
base_model: NbAiLab/nb-gpt-j-6B-v2
model-index:
- name: aftonposten-6b-align-scan
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. -->
# aftonposten-6b-align-scan
This model is a fine-tuned version of [NbAiLab/nb-gpt-j-6B-v2](https://huggingface.co./NbAiLab/nb-gpt-j-6B-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6820
- Rewards/chosen: -0.2813
- Rewards/rejected: -0.4578
- Rewards/accuracies: 0.5743
- Rewards/margins: 0.1765
- Logps/rejected: -38.0889
- Logps/chosen: -34.3862
- Logits/rejected: -2.1265
- Logits/chosen: -2.1312
## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_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: 4
### Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.6538 | 0.26 | 100 | -2.2339 | -2.2290 | -34.0302 | -37.5273 | 0.6955 | 0.5108 | 0.0035 | 0.0120 | -0.0085 |
| 0.6015 | 0.52 | 200 | -2.2322 | -2.2274 | -34.0607 | -37.5657 | 0.6956 | 0.5249 | -0.0209 | 0.0183 | -0.0393 |
| 0.5385 | 0.78 | 300 | -2.2294 | -2.2246 | -34.0909 | -37.5973 | 0.6957 | 0.5399 | -0.0451 | 0.0194 | -0.0645 |
| 0.4017 | 1.04 | 400 | 0.6775 | -0.0241 | -0.0945 | 0.6005 | 0.0703 | -37.6347 | -34.0647 | -2.2052 | -2.2100 |
| 0.3216 | 1.3 | 500 | 0.6820 | -0.1165 | -0.2131 | 0.5768 | 0.0966 | -37.7830 | -34.1802 | -2.1659 | -2.1707 |
| 0.336 | 1.56 | 600 | 0.6618 | -0.1839 | -0.3388 | 0.6242 | 0.1549 | -37.9401 | -34.2644 | -2.1554 | -2.1602 |
| 0.3559 | 1.82 | 700 | 0.6947 | -0.2571 | -0.3713 | 0.5341 | 0.1141 | -37.9807 | -34.3560 | -2.1535 | -2.1583 |
| 0.1978 | 2.08 | 800 | 0.6838 | -0.2324 | -0.3669 | 0.5835 | 0.1345 | -37.9753 | -34.3250 | -2.1501 | -2.1549 |
| 0.1619 | 2.34 | 900 | 0.6788 | -0.2463 | -0.4156 | 0.5860 | 0.1693 | -38.0361 | -34.3424 | -2.1384 | -2.1431 |
| 0.209 | 2.6 | 1000 | 0.6777 | -0.2767 | -0.4535 | 0.5918 | 0.1767 | -38.0835 | -34.3805 | -2.1309 | -2.1357 |
| 0.2513 | 2.86 | 1100 | 0.6897 | -0.2986 | -0.4591 | 0.5831 | 0.1605 | -38.0905 | -34.4077 | -2.1270 | -2.1317 |
| 0.1713 | 3.12 | 1200 | 0.6780 | -0.2775 | -0.4614 | 0.5947 | 0.1839 | -38.0934 | -34.3814 | -2.1270 | -2.1317 |
| 0.1199 | 3.38 | 1300 | 0.6740 | -0.2726 | -0.4645 | 0.5980 | 0.1919 | -38.0972 | -34.3753 | -2.1269 | -2.1317 |
| 0.1578 | 3.64 | 1400 | 0.6839 | -0.2867 | -0.4600 | 0.5860 | 0.1734 | -38.0917 | -34.3929 | -2.1266 | -2.1314 |
| 0.1614 | 3.9 | 1500 | 0.6820 | -0.2813 | -0.4578 | 0.5743 | 0.1765 | -38.0889 | -34.3862 | -2.1265 | -2.1312 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 |