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---
library_name: peft
tags:
- trl
- dpo
- 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: 0.9713
- Rewards/chosen: -0.0468
- Rewards/rejected: -0.0779
- Rewards/accuracies: 0.5282
- Rewards/margins: 0.0310
- Logps/rejected: -37.6032
- Logps/chosen: -34.0866
- Logits/rejected: -2.2201
- Logits/chosen: -2.2249
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.8913 | 0.26 | 100 | 0.9845 | -0.0055 | -0.0215 | 0.5195 | 0.0159 | -37.5405 | -34.0407 | -2.2273 | -2.2322 |
| 0.7293 | 0.52 | 200 | 0.9602 | -0.0172 | -0.0580 | 0.5714 | 0.0408 | -37.5811 | -34.0537 | -2.2238 | -2.2286 |
| 0.6144 | 0.78 | 300 | 0.9713 | -0.0468 | -0.0779 | 0.5282 | 0.0310 | -37.6032 | -34.0866 | -2.2201 | -2.2249 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 |