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mistral_dpo2
underactuated/mistral_dpo2
mistral_dpo2 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 26, 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 26, 2024
- Updated
- Jul 26, 2024
- SHA
- a0d617ba
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_dpo2
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: 0.6594
- Rewards/chosen: -0.0073
- Rewards/rejected: -0.0880
- Rewards/accuracies: 0.6532
- Rewards/margins: 0.0807
- Logps/rejected: -47.9164
- Logps/chosen: -70.6164
- Logits/rejected: -0.6606
- Logits/chosen: -0.8711
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6886 | 0.1251 | 40 | 0.6857 | 0.0161 | 0.0006 | 0.6532 | 0.0154 | -47.0302 | -70.3825 | -0.6637 | -0.8738 |
| 0.6729 | 0.2502 | 80 | 0.6731 | 0.0155 | -0.0284 | 0.6587 | 0.0438 | -47.3201 | -70.3884 | -0.6620 | -0.8723 |
| 0.6661 | 0.3753 | 120 | 0.6656 | 0.0214 | -0.0413 | 0.6532 | 0.0627 | -47.4494 | -70.3287 | -0.6616 | -0.8720 |
| 0.6495 | 0.5004 | 160 | 0.6611 | -0.0187 | -0.0942 | 0.6532 | 0.0756 | -47.9787 | -70.7297 | -0.6609 | -0.8713 |
| 0.6525 | 0.6255 | 200 | 0.6594 | -0.0073 | -0.0880 | 0.6532 | 0.0807 | -47.9164 | -70.6164 | -0.6606 | -0.8711 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.2
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 26, 2024
- Updated
- Jul 26, 2024