metadata
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: NbAiLab/nb-gpt-j-6B-v2
datasets:
- hugodk-sch/aftonposten_title_prefs
model-index:
- name: aftonposten-6b-align-scan
results: []
aftonposten-6b-align-scan
This model is a fine-tuned version of data/ap-gpt-j-6b-sft-qlora-04-08 on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set:
- Loss: 6.0779
- Rewards/chosen: -0.0133
- Rewards/rejected: -0.0383
- Rewards/accuracies: 0.5714
- Rewards/margins: 0.0250
- Logps/rejected: -37.7083
- Logps/chosen: -34.1011
- Logits/rejected: -2.2004
- Logits/chosen: -2.2052
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 5.6745 | 0.26 | 100 | -2.2338 | -2.2290 | -34.0153 | -37.5181 | 6.2508 | 0.5461 | 0.0038 | 0.0041 | -0.0003 |
| 5.2135 | 0.52 | 200 | -2.2315 | -2.2267 | -34.0014 | -37.5042 | 6.2881 | 0.5403 | 0.0066 | 0.0041 | 0.0025 |
| 4.3883 | 0.78 | 300 | -2.2291 | -2.2243 | -34.0193 | -37.5325 | 6.2382 | 0.5166 | 0.0031 | 0.0062 | -0.0032 |
| 2.9753 | 1.04 | 400 | 6.0369 | 0.0069 | -0.0106 | 0.6034 | 0.0176 | -37.5698 | -33.9999 | -2.2093 | -2.2141 |
| 2.4163 | 1.3 | 500 | 6.0677 | -0.0149 | -0.0375 | 0.5801 | 0.0225 | -37.7039 | -34.1092 | -2.1858 | -2.1907 |
| 2.52 | 1.56 | 600 | 5.9990 | -0.0097 | -0.0348 | 0.5748 | 0.0251 | -37.6905 | -34.0832 | -2.1951 | -2.1999 |
| 2.9186 | 1.82 | 700 | 6.1696 | -0.0176 | -0.0364 | 0.5598 | 0.0188 | -37.6988 | -34.1227 | -2.2048 | -2.2097 |
| 1.2867 | 2.08 | 800 | 6.0594 | -0.0122 | -0.0361 | 0.5777 | 0.0239 | -37.6970 | -34.0957 | -2.2060 | -2.2109 |
| 0.8862 | 2.34 | 900 | 6.0621 | -0.0165 | -0.0403 | 0.5918 | 0.0237 | -37.7179 | -34.1172 | -2.2027 | -2.2076 |
| 1.2395 | 2.6 | 1000 | 6.0000 | -0.0163 | -0.0418 | 0.5864 | 0.0255 | -37.7257 | -34.1161 | -2.2002 | -2.2050 |
| 1.4312 | 2.86 | 1100 | 5.9905 | -0.0144 | -0.0409 | 0.5860 | 0.0264 | -37.7210 | -34.1067 | -2.1989 | -2.2038 |
| 1.0133 | 3.12 | 1200 | 6.1103 | -0.0167 | -0.0396 | 0.5889 | 0.0229 | -37.7146 | -34.1182 | -2.2000 | -2.2048 |
| 0.5152 | 3.38 | 1300 | 6.0578 | -0.0132 | -0.0383 | 0.5544 | 0.0251 | -37.7080 | -34.1004 | -2.2003 | -2.2051 |
| 0.8378 | 3.64 | 1400 | 6.0572 | -0.0138 | -0.0389 | 0.5748 | 0.0251 | -37.7113 | -34.1035 | -2.2004 | -2.2052 |
| 0.9599 | 3.9 | 1500 | 6.0348 | -0.0125 | -0.0385 | 0.5835 | 0.0260 | -37.7091 | -34.0972 | -2.2004 | -2.2052 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1