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mistral_dpo3
underactuated/mistral_dpo3
mistral_dpo3 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 31, 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 31, 2024
- Updated
- Jul 31, 2024
- SHA
- cad926c0
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_dpo3
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: 0.6493
- Rewards/chosen: -0.0199
- Rewards/rejected: -0.1207
- Rewards/accuracies: 0.6902
- Rewards/margins: 0.1008
- Logps/rejected: -49.8290
- Logps/chosen: -78.6185
- Logits/rejected: -0.5023
- Logits/chosen: -0.7841
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6892 | 0.1236 | 40 | 0.6854 | -0.0095 | -0.0254 | 0.6975 | 0.0159 | -48.8761 | -78.5142 | -0.5066 | -0.7881 |
| 0.6746 | 0.2473 | 80 | 0.6703 | 0.0082 | -0.0405 | 0.6957 | 0.0487 | -49.0272 | -78.3371 | -0.5048 | -0.7865 |
| 0.6579 | 0.3709 | 120 | 0.6587 | 0.0022 | -0.0744 | 0.6938 | 0.0766 | -49.3662 | -78.3975 | -0.5036 | -0.7854 |
| 0.6539 | 0.4946 | 160 | 0.6516 | -0.0128 | -0.1074 | 0.6902 | 0.0946 | -49.6963 | -78.5475 | -0.5026 | -0.7844 |
| 0.6464 | 0.6182 | 200 | 0.6493 | -0.0199 | -0.1207 | 0.6902 | 0.1008 | -49.8290 | -78.6185 | -0.5023 | -0.7841 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 31, 2024
- Updated
- Jul 31, 2024