metadata
license: mit
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi3-offline-dpo-lora-noise-0.0-5e-6-42
results: []
phi3-offline-dpo-lora-noise-0.0-5e-6-42
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6639
- Rewards/chosen: -0.1248
- Rewards/rejected: -0.1933
- Rewards/accuracies: 0.7421
- Rewards/margins: 0.0685
- Logps/rejected: -403.0595
- Logps/chosen: -421.0499
- Logits/rejected: 12.1072
- Logits/chosen: 13.9087
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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 |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6931 | 0.1778 | 100 | 0.6835 | -0.0511 | -0.0728 | 0.6905 | 0.0218 | -391.0186 | -413.6780 | 12.3764 | 14.1803 |
0.689 | 0.3556 | 200 | 0.6682 | -0.1441 | -0.2014 | 0.7460 | 0.0573 | -403.8743 | -422.9761 | 12.1803 | 13.9841 |
0.6923 | 0.5333 | 300 | 0.6673 | -0.1140 | -0.1749 | 0.7897 | 0.0609 | -401.2295 | -419.9747 | 12.1769 | 13.9748 |
0.6914 | 0.7111 | 400 | 0.6655 | -0.1195 | -0.1839 | 0.7698 | 0.0644 | -402.1236 | -420.5240 | 12.1267 | 13.9317 |
0.696 | 0.8889 | 500 | 0.6633 | -0.1262 | -0.1959 | 0.7540 | 0.0697 | -403.3280 | -421.1901 | 12.0952 | 13.8997 |
Framework versions
- PEFT 0.7.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1