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openhermes-mistral-dpo-gptq
KaleDivergence/openhermes-mistral-dpo-gptq
openhermes-mistral-dpo-gptq is a machine learning model from KaleDivergence. 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 Dec 7, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 7, 2023
- Updated
- Dec 7, 2023
- SHA
- 6ea02867
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: 0.6671
- Rewards/chosen: -0.4223
- Rewards/rejected: -1.9854
- Rewards/accuracies: 0.4375
- Rewards/margins: 1.5631
- Logps/rejected: -350.5416
- Logps/chosen: -220.8451
- Logits/rejected: -1.7880
- Logits/chosen: -1.7651
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6968 | 0.01 | 10 | 0.6686 | -0.0503 | -0.0549 | 0.5625 | 0.0046 | -331.2371 | -217.1252 | -1.8320 | -1.8255 |
| 0.6793 | 0.01 | 20 | 1.7619 | 0.2100 | 3.0956 | 0.3125 | -2.8856 | -299.7324 | -214.5222 | -1.9578 | -1.9436 |
| 0.6789 | 0.01 | 30 | 0.6364 | -0.2040 | -1.0884 | 0.4375 | 0.8843 | -341.5715 | -218.6622 | -1.8060 | -1.7894 |
| 0.6966 | 0.02 | 40 | 0.6716 | -0.2823 | -1.4572 | 0.4375 | 1.1749 | -345.2603 | -219.4454 | -1.7994 | -1.7786 |
| 0.8051 | 0.03 | 50 | 0.6671 | -0.4223 | -1.9854 | 0.4375 | 1.5631 | -350.5416 | -220.8451 | -1.7880 | -1.7651 |
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 7, 2023
- Updated
- Dec 7, 2023