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: 1.0237
- Rewards/chosen: -0.0663
- Rewards/rejected: -0.1206
- Rewards/accuracies: 0.5311
- Rewards/margins: 0.0543
- Logps/rejected: -36.1388
- Logps/chosen: -32.5378
- Logits/rejected: 98.6966
- Logits/chosen: 98.7185
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.9161 | 0.26 | 100 | 1.0662 | -0.0346 | -0.0243 | 0.5129 | -0.0103 | -36.0012 | -32.4926 | 98.7623 | 98.7729 |
| 0.8398 | 0.52 | 200 | 1.0090 | -0.1355 | -0.2279 | 0.5141 | 0.0924 | -36.2922 | -32.6368 | 98.6916 | 98.7167 |
| 0.733 | 0.78 | 300 | 1.0124 | -0.0636 | -0.1409 | 0.5399 | 0.0773 | -36.1679 | -32.5340 | 98.7098 | 98.7339 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1