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phi-2-gpo-newSFT-b0.001-i0
DUAL-GPO/phi-2-gpo-newSFT-b0.001-i0
phi-2-gpo-newSFT-b0.001-i0 is a machine learning model from DUAL-GPO. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Model type
- phi
- Access
- Public
- Created
- May 10, 2024
- Updated
- May 10, 2024
- SHA
- 7c924ba2
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
phi-2-gpo-newSFT-b0.001-i0
This model is a fine-tuned version of DUAL-GPO/phi-2-sft-lora-ultrachat-merged on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0401
- Rewards/chosen: -0.0556
- Rewards/rejected: -0.0895
- Rewards/accuracies: 0.6018
- Rewards/margins: 0.0338
- Logps/rejected: -337.8973
- Logps/chosen: -325.6151
- Logits/rejected: 0.2226
- Logits/chosen: 0.1916
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: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 12
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0569 | 0.08 | 100 | 0.0535 | 0.0003 | -0.0004 | 0.5973 | 0.0006 | -248.8037 | -269.7070 | 1.0547 | 0.9877 |
| 0.0565 | 0.16 | 200 | 0.0515 | -0.0016 | -0.0068 | 0.6078 | 0.0052 | -255.2234 | -271.5318 | 0.9706 | 0.8998 |
| 0.0467 | 0.24 | 300 | 0.0470 | -0.0316 | -0.0485 | 0.6033 | 0.0169 | -296.9762 | -301.5743 | 0.5528 | 0.4973 |
| 0.0467 | 0.31 | 400 | 0.0443 | -0.0370 | -0.0583 | 0.6033 | 0.0213 | -306.7241 | -306.9802 | 0.3457 | 0.3071 |
| 0.0359 | 0.39 | 500 | 0.0428 | -0.0574 | -0.0869 | 0.5988 | 0.0296 | -335.3609 | -327.3275 | 0.2119 | 0.1835 |
| 0.0431 | 0.47 | 600 | 0.0418 | -0.0450 | -0.0725 | 0.6033 | 0.0275 | -320.9161 | -314.9630 | 0.2891 | 0.2554 |
| 0.0438 | 0.55 | 700 | 0.0413 | -0.0574 | -0.0889 | 0.6018 | 0.0316 | -337.3519 | -327.3254 | 0.2356 | 0.2040 |
| 0.0446 | 0.63 | 800 | 0.0409 | -0.0522 | -0.0842 | 0.6048 | 0.0320 | -332.6603 | -322.1777 | 0.2566 | 0.2236 |
| 0.0426 | 0.71 | 900 | 0.0408 | -0.0624 | -0.0977 | 0.6048 | 0.0353 | -346.1494 | -332.3424 | 0.2089 | 0.1797 |
| 0.0448 | 0.79 | 1000 | 0.0403 | -0.0545 | -0.0869 | 0.6063 | 0.0324 | -335.3596 | -324.4480 | 0.2463 | 0.2141 |
| 0.0411 | 0.86 | 1100 | 0.0402 | -0.0549 | -0.0884 | 0.6018 | 0.0336 | -336.8657 | -324.8257 | 0.2283 | 0.1971 |
| 0.0459 | 0.94 | 1200 | 0.0401 | -0.0558 | -0.0896 | 0.6033 | 0.0338 | -338.0042 | -325.7257 | 0.2205 | 0.1898 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
- Library
- peft
- Type
- phi
- Created
- May 10, 2024
- Updated
- May 10, 2024