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: 0.9524
- Rewards/chosen: -0.0816
- Rewards/rejected: -0.1313
- Rewards/accuracies: 0.5303
- Rewards/margins: 0.0497
- Logps/rejected: -36.6233
- Logps/chosen: -32.8513
- Logits/rejected: 98.1886
- Logits/chosen: 98.2171
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.927 | 0.26 | 100 | 0.9734 | 0.0205 | -0.0061 | 0.5598 | 0.0265 | -35.9968 | -32.3408 | 98.7115 | 98.7190 |
| 0.7448 | 0.52 | 200 | 0.9482 | -0.0840 | -0.1367 | 0.5307 | 0.0527 | -36.6501 | -32.8631 | 98.2057 | 98.2271 |
| 0.7402 | 0.78 | 300 | 0.9400 | -0.0802 | -0.1425 | 0.5623 | 0.0624 | -36.6792 | -32.8440 | 98.1900 | 98.2178 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1