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mistral_dpo
underactuated/mistral_dpo
mistral_dpo 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 Jun 24, 2024
Repo size
1.7 GB
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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
- Jun 11, 2024
- Updated
- Jun 24, 2024
- SHA
- 16532495
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_dpo
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: 0.6891
- Rewards/chosen: 0.0621
- Rewards/rejected: 0.0538
- Rewards/accuracies: 0.6213
- Rewards/margins: 0.0083
- Logps/rejected: -52.0979
- Logps/chosen: -55.7624
- Logits/rejected: -0.2991
- Logits/chosen: -0.3269
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: 20
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6929 | 0.0882 | 20 | 0.6923 | 0.0239 | 0.0221 | 0.6109 | 0.0018 | -52.4151 | -56.1451 | -0.2993 | -0.3271 |
| 0.6919 | 0.1763 | 40 | 0.6908 | 0.0490 | 0.0443 | 0.6187 | 0.0047 | -52.1927 | -55.8934 | -0.2991 | -0.3268 |
| 0.6903 | 0.2645 | 60 | 0.6898 | 0.0587 | 0.0518 | 0.6157 | 0.0068 | -52.1173 | -55.7971 | -0.2991 | -0.3269 |
| 0.6899 | 0.3526 | 80 | 0.6892 | 0.0595 | 0.0515 | 0.6135 | 0.0081 | -52.1210 | -55.7885 | -0.2991 | -0.3269 |
| 0.6898 | 0.4408 | 100 | 0.6891 | 0.0621 | 0.0538 | 0.6213 | 0.0083 | -52.0979 | -55.7624 | -0.2991 | -0.3269 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jun 11, 2024
- Updated
- Jun 24, 2024