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-extra-v2-i1
results: []
phi-2-gpo-renew2-b0.001-extra-v2-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: 0.0388
- Rewards/chosen: 0.0266
- Rewards/rejected: -0.0126
- Rewards/accuracies: 0.6070
- Rewards/margins: 0.0392
- Logps/rejected: -379.8497
- Logps/chosen: -369.7509
- Logits/rejected: -0.9196
- Logits/chosen: -0.9539
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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.098 | 0.06 | 100 | 0.0533 | -0.0029 | -0.0036 | 0.4980 | 0.0007 | -370.8433 | -399.2503 | -0.7225 | -0.8171 |
| 0.094 | 0.13 | 200 | 0.0491 | -0.0390 | -0.0525 | 0.5525 | 0.0135 | -419.6949 | -435.2693 | -1.0754 | -1.1388 |
| 0.0898 | 0.19 | 300 | 0.0452 | -0.0184 | -0.0403 | 0.5780 | 0.0218 | -407.5088 | -414.7480 | -1.0291 | -1.0858 |
| 0.0731 | 0.26 | 400 | 0.0430 | -0.0069 | -0.0331 | 0.5970 | 0.0262 | -400.2979 | -403.1916 | -0.9864 | -1.0412 |
| 0.0787 | 0.32 | 500 | 0.0422 | -0.0122 | -0.0473 | 0.6070 | 0.0351 | -414.4887 | -408.4566 | -1.0587 | -1.0975 |
| 0.0742 | 0.38 | 600 | 0.0406 | 0.0135 | -0.0175 | 0.6085 | 0.0309 | -384.7105 | -382.8363 | -0.9872 | -1.0246 |
| 0.0635 | 0.45 | 700 | 0.0401 | 0.0166 | -0.0188 | 0.6095 | 0.0354 | -386.0258 | -379.6696 | -0.9903 | -1.0225 |
| 0.0881 | 0.51 | 800 | 0.0395 | 0.0250 | -0.0102 | 0.6085 | 0.0352 | -377.4323 | -371.2672 | -0.9658 | -0.9975 |
| 0.0753 | 0.58 | 900 | 0.0393 | 0.0304 | -0.0046 | 0.5990 | 0.0350 | -371.7872 | -365.8699 | -0.9026 | -0.9456 |
| 0.0922 | 0.64 | 1000 | 0.0390 | 0.0286 | -0.0075 | 0.5990 | 0.0361 | -374.7669 | -367.7319 | -0.8801 | -0.9184 |
| 0.0703 | 0.7 | 1100 | 0.0389 | 0.0227 | -0.0161 | 0.6000 | 0.0387 | -383.3026 | -373.6226 | -0.9300 | -0.9602 |
| 0.0746 | 0.77 | 1200 | 0.0388 | 0.0226 | -0.0179 | 0.6050 | 0.0405 | -385.1601 | -373.7153 | -0.8944 | -0.9306 |
| 0.0925 | 0.83 | 1300 | 0.0387 | 0.0263 | -0.0131 | 0.6030 | 0.0393 | -380.3072 | -370.0340 | -0.9171 | -0.9494 |
| 0.0863 | 0.9 | 1400 | 0.0387 | 0.0269 | -0.0123 | 0.6055 | 0.0392 | -379.5608 | -369.4450 | -0.9121 | -0.9447 |
| 0.0904 | 0.96 | 1500 | 0.0386 | 0.0268 | -0.0124 | 0.6045 | 0.0392 | -379.6000 | -369.4944 | -0.9203 | -0.9536 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2