Downloads · 30 days
0
openhermes-mistral-dpo-gptq
aiworks/openhermes-mistral-dpo-gptq
openhermes-mistral-dpo-gptq is a machine learning model from aiworks. 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. --
Access
Public
Updated Dec 8, 2023
Repo size
14.2 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors13.6 MB · 86%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 8, 2023
- Updated
- Dec 8, 2023
- SHA
- 97b51ffc
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: 0.5481
- Rewards/chosen: -6.3042
- Rewards/rejected: -6.6831
- Rewards/accuracies: 0.3125
- Rewards/margins: 0.3789
- Logps/rejected: -270.7899
- Logps/chosen: -222.5794
- Logits/rejected: -2.0400
- Logits/chosen: -2.0341
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6859 | 0.01 | 10 | 0.6666 | 0.0119 | -0.0301 | 0.5 | 0.0419 | -204.2597 | -159.4191 | -2.1849 | -2.1781 |
| 0.683 | 0.01 | 20 | 0.6372 | 0.0384 | -0.0380 | 0.3125 | 0.0763 | -204.3386 | -159.1542 | -2.1870 | -2.1765 |
| 0.7067 | 0.01 | 30 | 0.6194 | 0.0592 | -0.0362 | 0.3125 | 0.0954 | -204.3213 | -158.9460 | -2.1880 | -2.1773 |
| 0.6664 | 0.02 | 40 | 0.6159 | 0.0599 | -0.0264 | 0.3125 | 0.0862 | -204.2225 | -158.9388 | -2.1856 | -2.1759 |
| 0.786 | 0.03 | 50 | 0.5481 | -6.3042 | -6.6831 | 0.3125 | 0.3789 | -270.7899 | -222.5794 | -2.0400 | -2.0341 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Dec 8, 2023
- Updated
- Dec 8, 2023