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phi-2-sft-dpo-gpt4_en-ep1-lora
Yhyu13/phi-2-sft-dpo-gpt4_en-ep1-lora
phi-2-sft-dpo-gpt4_en-ep1-lora is a machine learning model from Yhyu13. 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. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Dec 22, 2023
- Updated
- Dec 22, 2023
- SHA
- fdbe3584
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-sft-alpaca_gpt4_en-ep1-dpo-comparison_gpt4_en-ep1-lora
This model is a fine-tuned version of Yhyu13/phi-2-sft-alpaca_gpt4_en-ep1 on the comparison_gpt4_en dataset. It achieves the following results on the evaluation set:
- Loss: 0.0168
- Rewards/chosen: -1.5750
- Rewards/rejected: -11.4002
- Rewards/accuracies: 0.9956
- Rewards/margins: 9.8253
- Logps/rejected: -142.2352
- Logps/chosen: -139.5300
- Logits/rejected: 0.6066
- Logits/chosen: 0.9744
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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0534 | 0.24 | 1000 | 0.0217 | -1.6714 | -10.2359 | 0.9945 | 8.5645 | -130.5921 | -140.4941 | 0.3064 | 0.5735 |
| 0.0182 | 0.49 | 2000 | 0.0175 | -1.5469 | -10.9602 | 0.9951 | 9.4133 | -137.8349 | -139.2487 | 0.6230 | 1.0709 |
| 0.0162 | 0.73 | 3000 | 0.0171 | -1.5517 | -11.4444 | 0.9962 | 9.8927 | -142.6772 | -139.2976 | 0.6325 | 1.0048 |
| 0.0154 | 0.98 | 4000 | 0.0168 | -1.5741 | -11.4004 | 0.9956 | 9.8262 | -142.2364 | -139.5214 | 0.6051 | 0.9729 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
- Library
- peft
- License
- other
- Created
- Dec 22, 2023
- Updated
- Dec 22, 2023