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Mistral-7B-Instruct-v0.2-multilingual-dpo-v1.0-v2
nthakur/Mistral-7B-Instruct-v0.2-multilingual-dpo-v1.0-v2
Mistral-7B-Instruct-v0.2-multilingual-dpo-v1.0-v2 is a machine learning model from nthakur. 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
- Model type
- mistral
- Access
- Public
- Created
- Aug 22, 2024
- Updated
- Aug 23, 2024
- SHA
- 288c6525
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-7B-Instruct-v0.2-multilingual-dpo-v1.0-v2
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the nthakur/multilingual-ultrafeedback-binarized-dpo-v0.1, the nthakur/multilingual-distilabel-intel-orca-dpo-pairs-v0.1, the nthakur/multilingual-truthy-dpo-pairs-v0.1 and the nthakur/GSM8KInstruct-Parallel-instruct-dpo-v0.1 datasets. It achieves the following results on the evaluation set:
- Loss: 0.1324
- Rewards/chosen: -2.6738
- Rewards/rejected: -12.2394
- Rewards/accuracies: 0.9377
- Rewards/margins: 9.5656
- Logps/rejected: -1515.8665
- Logps/chosen: -607.0774
- Logits/rejected: 0.4952
- Logits/chosen: 0.3030
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2695 | 0.1361 | 500 | 0.2653 | -0.4399 | -4.5379 | 0.8680 | 4.0981 | -745.7153 | -383.6803 | -1.3998 | -1.5327 |
| 0.4349 | 0.2723 | 1000 | 0.3152 | -2.6018 | -7.1212 | 0.8515 | 4.5195 | -1004.0471 | -599.8698 | 4.1724 | 4.7868 |
| 0.531 | 0.4084 | 1500 | 0.4873 | -2.4253 | -8.0681 | 0.7855 | 5.6428 | -1098.7278 | -582.2241 | -1.5195 | -1.6538 |
| 0.1681 | 0.5446 | 2000 | 0.2003 | -3.9555 | -13.1169 | 0.9089 | 9.1613 | -1603.6106 | -735.2488 | -0.1888 | -0.3742 |
| 0.1778 | 0.6807 | 2500 | 0.2004 | -3.4745 | -11.9768 | 0.9242 | 8.5023 | -1489.6012 | -687.1464 | -0.7118 | -0.9608 |
| 0.1342 | 0.8169 | 3000 | 0.1452 | -3.0928 | -12.8477 | 0.9340 | 9.7549 | -1576.6960 | -648.9738 | 0.6727 | 0.5428 |
| 0.1252 | 0.9530 | 3500 | 0.1328 | -2.7014 | -12.3976 | 0.9383 | 9.6962 | -1531.6849 | -609.8344 | 0.5002 | 0.3026 |
Framework versions
- PEFT 0.7.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- Type
- mistral
- License
- apache-2.0
- Created
- Aug 22, 2024
- Updated
- Aug 23, 2024