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openhermes-mistral-dpo-gptq
jdang/openhermes-mistral-dpo-gptq
openhermes-mistral-dpo-gptq is a machine learning model from jdang. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Jan 20, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jan 12, 2024
- Updated
- Jan 20, 2024
- SHA
- 35464197
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. -->
openhermes-mistral-dpo-gptq
This model is a fine-tuned version of TheBloke/OpenHermes-2-Mistral-7B-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6104
- Rewards/chosen: -0.0458
- Rewards/rejected: -0.4535
- Rewards/accuracies: 0.6875
- Rewards/margins: 0.4077
- Logps/rejected: -390.3771
- Logps/chosen: -149.5892
- Logits/rejected: -1.3692
- Logits/chosen: -1.4352
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: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6865 | 0.01 | 10 | 0.6792 | -0.0093 | -0.0078 | 0.6875 | -0.0015 | -385.9200 | -149.2238 | -1.3698 | -1.4189 |
| 0.6882 | 0.01 | 20 | 0.6660 | -0.0137 | -0.0526 | 0.625 | 0.0389 | -386.3681 | -149.2680 | -1.3729 | -1.4240 |
| 0.6391 | 0.01 | 30 | 0.6446 | 0.0000 | -0.1131 | 0.625 | 0.1131 | -386.9731 | -149.1310 | -1.3737 | -1.4292 |
| 0.639 | 0.02 | 40 | 0.6271 | -0.0337 | -0.2758 | 0.6875 | 0.2421 | -388.6000 | -149.4686 | -1.3729 | -1.4342 |
| 0.6533 | 0.03 | 50 | 0.6104 | -0.0458 | -0.4535 | 0.6875 | 0.4077 | -390.3771 | -149.5892 | -1.3692 | -1.4352 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Jan 12, 2024
- Updated
- Jan 20, 2024