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dpo-model-lora
lewtun/dpo-model-lora
dpo-model-lora is a machine learning model from lewtun. 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
- Access
- Public
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024
- SHA
- aefb0c8d
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. -->
dpo-model-lora
This model is a fine-tuned version of Qwen/Qwen2-0.5B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6534
- Rewards/chosen: -0.7320
- Rewards/rejected: -0.8303
- Rewards/accuracies: 0.6172
- Rewards/margins: 0.0983
- Logps/rejected: -359.0921
- Logps/chosen: -378.4928
- Logits/rejected: -2.2715
- Logits/chosen: -2.3471
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: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6884 | 0.1030 | 50 | 0.6879 | -0.0543 | -0.0734 | 0.6484 | 0.0191 | -351.5229 | -371.7161 | -2.2877 | -2.3628 |
| 0.6787 | 0.2060 | 100 | 0.6770 | -0.1811 | -0.2114 | 0.6016 | 0.0303 | -352.9030 | -372.9836 | -2.2815 | -2.3565 |
| 0.6721 | 0.3090 | 150 | 0.6721 | -0.2679 | -0.3094 | 0.6562 | 0.0415 | -353.8831 | -373.8524 | -2.2782 | -2.3536 |
| 0.6668 | 0.4119 | 200 | 0.6665 | -0.4037 | -0.4625 | 0.6016 | 0.0588 | -355.4139 | -375.2100 | -2.2758 | -2.3515 |
| 0.6597 | 0.5149 | 250 | 0.6612 | -0.4907 | -0.5505 | 0.6172 | 0.0598 | -356.2946 | -376.0805 | -2.2757 | -2.3510 |
| 0.6581 | 0.6179 | 300 | 0.6578 | -0.6137 | -0.6975 | 0.625 | 0.0838 | -357.7639 | -377.3098 | -2.2736 | -2.3491 |
| 0.6536 | 0.7209 | 350 | 0.6556 | -0.6458 | -0.7367 | 0.6328 | 0.0909 | -358.1565 | -377.6311 | -2.2732 | -2.3489 |
| 0.6486 | 0.8239 | 400 | 0.6556 | -0.7025 | -0.7958 | 0.6328 | 0.0933 | -358.7473 | -378.1981 | -2.2737 | -2.3493 |
| 0.649 | 0.9269 | 450 | 0.6556 | -0.7432 | -0.8327 | 0.6484 | 0.0896 | -359.1166 | -378.6048 | -2.2726 | -2.3482 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024