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mistral_dpo1
underactuated/mistral_dpo1
mistral_dpo1 is a machine learning model from underactuated. 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. --
Access
Public
Updated Jul 23, 2024
Repo size
336 MB
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Repo makeup
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.safetensors336 MB · 99%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024
- SHA
- 2c21c2ff
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. -->
mistral_dpo1
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6658
- Rewards/chosen: 0.2577
- Rewards/rejected: 0.1951
- Rewards/accuracies: 0.6588
- Rewards/margins: 0.0625
- Logps/rejected: -48.8060
- Logps/chosen: -74.7955
- Logits/rejected: -0.5381
- Logits/chosen: -0.8076
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6891 | 0.1598 | 40 | 0.6869 | 0.0983 | 0.0855 | 0.6470 | 0.0129 | -49.9027 | -76.3890 | -0.5382 | -0.8076 |
| 0.6782 | 0.3195 | 80 | 0.6772 | 0.2135 | 0.1789 | 0.6494 | 0.0346 | -48.9688 | -75.2377 | -0.5385 | -0.8080 |
| 0.6719 | 0.4793 | 120 | 0.6712 | 0.2187 | 0.1699 | 0.6635 | 0.0488 | -49.0587 | -75.1852 | -0.5383 | -0.8078 |
| 0.6635 | 0.6390 | 160 | 0.6675 | 0.2557 | 0.1974 | 0.6635 | 0.0584 | -48.7838 | -74.8149 | -0.5381 | -0.8077 |
| 0.655 | 0.7988 | 200 | 0.6658 | 0.2577 | 0.1951 | 0.6588 | 0.0625 | -48.8060 | -74.7955 | -0.5381 | -0.8076 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024