metadata
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: phi-2-gpo-renew2-b0.001-i1
results: []
phi-2-gpo-renew2-b0.001-i1
This model is a fine-tuned version of DUAL-GPO/phi-2-gpo-renew2-b0.001-i0 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0538
- Rewards/chosen: 0.0010
- Rewards/rejected: 0.0012
- Rewards/accuracies: 0.4290
- Rewards/margins: -0.0002
- Logps/rejected: -366.0280
- Logps/chosen: -395.2844
- Logits/rejected: -0.7463
- Logits/chosen: -0.8436
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
- gradient_accumulation_steps: 4
- total_train_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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1204 | 0.32 | 100 | -0.8372 | -0.7448 | -396.1279 | -367.0282 | 0.0537 | 0.4495 | 0.0002 | -0.0000 | 0.0002 |
| 0.1673 | 0.64 | 200 | 0.0538 | 0.0013 | 0.0015 | 0.4305 | -0.0002 | -365.7495 | -395.0410 | -0.7569 | -0.8518 |
| 0.1395 | 0.96 | 300 | 0.0538 | 0.0010 | 0.0012 | 0.4395 | -0.0002 | -365.9886 | -395.3006 | -0.7587 | -0.8541 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2