Downloads · 30 days
0
openhermes-mistral-dpo-gptq
ZoninSh/openhermes-mistral-dpo-gptq
openhermes-mistral-dpo-gptq is a machine learning model from ZoninSh. 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 Nov 18, 2023
Repo size
98.1 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors83.9 MB · 97%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 18, 2023
- Updated
- Nov 18, 2023
- SHA
- bdb85929
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: 3.2500
- Rewards/chosen: -1.0975
- Rewards/rejected: -1.6306
- Rewards/accuracies: 0.625
- Rewards/margins: 0.5331
- Logps/rejected: -307.3866
- Logps/chosen: -331.8629
- Logits/rejected: -2.4077
- Logits/chosen: -2.3038
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: 300
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 4.2921 | 0.03 | 50 | 9.8028 | -5.3862 | 0.1060 | 0.1875 | -5.4922 | -290.0201 | -374.7499 | -2.2861 | -2.1795 |
| 9.75 | 0.05 | 100 | 8.8191 | -12.7493 | -8.6505 | 0.3125 | -4.0989 | -377.5849 | -448.3811 | -2.2836 | -2.2309 |
| 3.2104 | 0.07 | 150 | 0.8915 | -3.5710 | -6.0350 | 0.375 | 2.4640 | -351.4305 | -356.5982 | -2.6543 | -2.5955 |
| 2.655 | 0.1 | 200 | 0.3207 | -1.0209 | -4.6027 | 0.6875 | 3.5818 | -337.1074 | -331.0971 | -2.4341 | -2.3534 |
| 4.8481 | 0.12 | 250 | 1.1311 | -0.8147 | -2.3072 | 0.625 | 1.4926 | -314.1525 | -329.0346 | -2.3257 | -2.2374 |
| 3.1598 | 0.15 | 300 | 3.2500 | -1.0975 | -1.6306 | 0.625 | 0.5331 | -307.3866 | -331.8629 | -2.4077 | -2.3038 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Nov 18, 2023
- Updated
- Nov 18, 2023