metadata
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: norallm/normistral-7b-warm
datasets:
- hugodk-sch/aftonposten_title_prefs
model-index:
- name: ap-normistral-7b-align-scan
results: []
ap-normistral-7b-align-scan
This model is a fine-tuned version of data/ap-normistral-7b-sft-qlora on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set:
- Loss: 0.4992
- Rewards/chosen: 0.0239
- Rewards/rejected: 0.0174
- Rewards/accuracies: 0.4892
- Rewards/margins: 0.0064
- Logps/rejected: -35.7921
- Logps/chosen: -32.2044
- Logits/rejected: 98.2668
- Logits/chosen: 98.2727
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4933 | 0.26 | 100 | 0.5023 | 0.0062 | 0.0168 | 0.4498 | -0.0106 | -35.7990 | -32.3816 | 98.6627 | 98.6788 |
| 0.4602 | 0.52 | 200 | 0.4967 | 0.0067 | -0.0120 | 0.5511 | 0.0188 | -36.0870 | -32.3759 | 98.3410 | 98.3552 |
| 0.4586 | 0.78 | 300 | 0.4994 | 0.0186 | 0.0126 | 0.5129 | 0.0060 | -35.8407 | -32.2572 | 98.2712 | 98.2791 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1