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zephyr-7b-dpo-qlora
jiangjun0105woven/zephyr-7b-dpo-qlora
zephyr-7b-dpo-qlora is a machine learning model from jiangjun0105woven. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Model type
- mistral
- Access
- Public
- Created
- Oct 18, 2024
- Updated
- Oct 25, 2024
- SHA
- cd1a3595
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 alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5020
- Rewards/chosen: -2.1712
- Rewards/rejected: -2.9620
- Rewards/accuracies: 0.7054
- Rewards/margins: 0.7908
- Logps/rejected: -535.7245
- Logps/chosen: -475.6829
- Logits/rejected: -1.1754
- Logits/chosen: -1.2812
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: 6
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- total_eval_batch_size: 24
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6099 | 0.1570 | 100 | 0.5999 | -0.4571 | -0.6755 | 0.6369 | 0.2184 | -307.0734 | -304.2707 | -2.1308 | -2.2191 |
| 0.5468 | 0.3140 | 200 | 0.5354 | -1.2063 | -1.7025 | 0.6815 | 0.4962 | -409.7740 | -379.1950 | -1.5157 | -1.6078 |
| 0.5195 | 0.4710 | 300 | 0.5227 | -1.5981 | -2.2831 | 0.7083 | 0.6849 | -467.8293 | -418.3782 | -1.3523 | -1.4527 |
| 0.4895 | 0.6279 | 400 | 0.5142 | -1.8555 | -2.6654 | 0.6994 | 0.8099 | -506.0622 | -444.1171 | -1.1070 | -1.2180 |
| 0.4992 | 0.7849 | 500 | 0.5019 | -2.3330 | -3.1029 | 0.7054 | 0.7699 | -549.8137 | -491.8629 | -1.1520 | -1.2589 |
| 0.5001 | 0.9419 | 600 | 0.5021 | -2.1712 | -2.9608 | 0.7083 | 0.7896 | -535.6057 | -475.6837 | -1.1768 | -1.2825 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.1.2
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- peft
- Type
- mistral
- License
- apache-2.0
- Created
- Oct 18, 2024
- Updated
- Oct 25, 2024