Downloads · 30 days
8
21% of all-time downloads
zephyr-7b-dpo-full-prometheus-3
sfulay/zephyr-7b-dpo-full-prometheus-3
zephyr-7b-dpo-full-prometheus-3 is a machine learning model from sfulay. 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. --
All-time downloads
39
Public
Parameters
7.2B
72.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors14.5 GB · 100%
At a glance
- License
- apache-2.0
- Model type
- mistral
- Access
- Public
- Created
- Aug 20, 2024
- Updated
- Aug 20, 2024
- SHA
- 36fafa09
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. -->
zephyr-7b-dpo-full-prometheus-3
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4961
- Rewards/chosen: -1.0197
- Rewards/rejected: -1.9078
- Rewards/accuracies: 0.7241
- Rewards/margins: 0.8881
- Logps/rejected: -439.0560
- Logps/chosen: -361.9284
- Logits/rejected: 2.1814
- Logits/chosen: 1.1464
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: 8
- eval_batch_size: 8
- seed: 55
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5621 | 0.2286 | 100 | 0.5630 | -0.6661 | -1.2098 | 0.6422 | 0.5437 | -369.2566 | -326.5674 | -0.4908 | -0.7741 |
| 0.5053 | 0.4571 | 200 | 0.5191 | -0.9978 | -1.7738 | 0.7241 | 0.7760 | -425.6610 | -359.7413 | 1.7795 | 1.0550 |
| 0.4913 | 0.6857 | 300 | 0.5001 | -1.0485 | -1.9070 | 0.7328 | 0.8584 | -438.9752 | -364.8153 | 2.0188 | 0.9765 |
| 0.5017 | 0.9143 | 400 | 0.4961 | -1.0197 | -1.9078 | 0.7241 | 0.8881 | -439.0560 | -361.9284 | 2.1814 | 1.1464 |
Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- mistral
- License
- apache-2.0
- Created
- Aug 20, 2024
- Updated
- Aug 20, 2024