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zephyr-7b-dpo-lora
diyali95916/zephyr-7b-dpo-lora
zephyr-7b-dpo-lora is a machine learning model from diyali95916. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Jan 28, 2024
Repo size
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At a glance
- License
- mit
- Access
- Public
- Created
- Dec 1, 2023
- Updated
- Jan 28, 2024
- SHA
- edf51ed1
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-lora
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6843
- Rewards/chosen: 0.0440
- Rewards/rejected: 0.0071
- Rewards/accuracies: 0.5
- Rewards/margins: 0.0369
- Logps/rejected: -132.8740
- Logps/chosen: -190.5722
- Logits/rejected: -2.2999
- Logits/chosen: -2.2747
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-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6931 | 0.55 | 1 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | -132.9451 | -191.0126 | -2.3015 | -2.2762 |
| 0.6931 | 1.66 | 3 | 0.6928 | 0.0185 | -0.0111 | 0.5 | 0.0296 | -133.0566 | -190.8279 | -2.3016 | -2.2755 |
| 0.6931 | 2.76 | 5 | 0.6843 | 0.0440 | 0.0071 | 0.5 | 0.0369 | -132.8740 | -190.5722 | -2.2999 | -2.2747 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- Dec 1, 2023
- Updated
- Jan 28, 2024