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zephyr-7b-dpo-qlora
statking/zephyr-7b-dpo-qlora
zephyr-7b-dpo-qlora is a machine learning model from statking. 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
- mistral
- Access
- Public
- Created
- May 17, 2024
- Updated
- May 17, 2024
- SHA
- 8cd58d77
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. -->
zephyr-7b-dpo-qlora
This model is a fine-tuned version of data/zephyr-7b-sft-qlora-merged on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.4935
- Rewards/chosen: -2.1676
- Rewards/rejected: -3.1735
- Rewards/accuracies: 0.7698
- Rewards/margins: 1.0059
- Logps/rejected: -564.1859
- Logps/chosen: -483.0326
- Logits/rejected: -1.4139
- Logits/chosen: -1.4811
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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6185 | 0.1047 | 100 | 0.6240 | -0.3010 | -0.5396 | 0.6964 | 0.2387 | -300.7997 | -296.3736 | -2.2954 | -2.3537 |
| 0.5724 | 0.2094 | 200 | 0.5692 | -0.8434 | -1.3284 | 0.7302 | 0.4850 | -379.6750 | -350.6113 | -2.2448 | -2.2930 |
| 0.5366 | 0.3141 | 300 | 0.5249 | -1.6887 | -2.4863 | 0.7639 | 0.7976 | -495.4648 | -435.1429 | -1.6220 | -1.6850 |
| 0.5397 | 0.4187 | 400 | 0.5253 | -1.2998 | -1.9923 | 0.7698 | 0.6925 | -446.0619 | -396.2537 | -1.7586 | -1.8144 |
| 0.5003 | 0.5234 | 500 | 0.5013 | -1.9982 | -2.9207 | 0.7659 | 0.9226 | -538.9065 | -466.0909 | -1.6049 | -1.6682 |
| 0.4835 | 0.6281 | 600 | 0.5027 | -2.5699 | -3.5168 | 0.7560 | 0.9470 | -598.5182 | -523.2593 | -1.3417 | -1.4125 |
| 0.4715 | 0.7328 | 700 | 0.4956 | -2.1902 | -3.1936 | 0.7679 | 1.0035 | -566.1955 | -485.2894 | -1.3782 | -1.4480 |
| 0.4898 | 0.8375 | 800 | 0.4948 | -2.0401 | -3.0116 | 0.7698 | 0.9715 | -547.9974 | -470.2821 | -1.4275 | -1.4946 |
| 0.4785 | 0.9422 | 900 | 0.4933 | -2.1713 | -3.1801 | 0.7738 | 1.0088 | -564.8470 | -483.4024 | -1.4105 | -1.4778 |
Framework versions
- PEFT 0.10.0
- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- mistral
- Created
- May 17, 2024
- Updated
- May 17, 2024