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---
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full
results: []
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/sanqiang/wdpo/runs/mswxqy0x)
# zephyr-7b-dpo-full
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0227
- Rewards/chosen: -2.3113
- Rewards/rejected: -2.8479
- Rewards/accuracies: 0.6931
- Rewards/margins: 0.5365
- Logps/rejected: -435.4867
- Logps/chosen: -375.3782
- Logits/rejected: -1.4622
- Logits/chosen: -1.5834
- Debug/policy Weights: 0.0374
- Debug/losses: 0.0212
- Debug/raw Losses: 0.5682
## 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: 42
- 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 | Debug/policy Weights | Debug/losses | Debug/raw Losses |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------------------:|:------------:|:----------------:|
| 0.1734 | 0.0796 | 100 | 0.1631 | -0.1425 | -0.1765 | 0.5924 | 0.0340 | -168.3475 | -158.4907 | -2.7043 | -2.7124 | 0.2381 | 0.1616 | 0.6787 |
| 0.0795 | 0.1592 | 200 | 0.0826 | -0.7160 | -0.9309 | 0.6483 | 0.2150 | -243.7922 | -215.8411 | -2.4879 | -2.4997 | 0.1266 | 0.0800 | 0.6296 |
| 0.0545 | 0.2388 | 300 | 0.0572 | -1.0974 | -1.4187 | 0.6642 | 0.3213 | -292.5661 | -253.9808 | -2.4160 | -2.4302 | 0.0894 | 0.0550 | 0.6166 |
| 0.0288 | 0.3183 | 400 | 0.0302 | -1.9563 | -2.3772 | 0.6698 | 0.4209 | -388.4184 | -339.8692 | -2.2376 | -2.2573 | 0.0477 | 0.0287 | 0.6044 |
| 0.0358 | 0.3979 | 500 | 0.0407 | -1.7169 | -2.1543 | 0.6698 | 0.4374 | -366.1241 | -315.9322 | -2.2265 | -2.2540 | 0.0659 | 0.0394 | 0.6064 |
| 0.0309 | 0.4775 | 600 | 0.0302 | -1.9504 | -2.4092 | 0.6660 | 0.4587 | -391.6147 | -339.2857 | -2.0849 | -2.1159 | 0.0489 | 0.0287 | 0.5899 |
| 0.0203 | 0.5571 | 700 | 0.0198 | -2.3315 | -2.7643 | 0.6856 | 0.4328 | -427.1261 | -377.3937 | -1.6613 | -1.7384 | 0.0317 | 0.0185 | 0.5808 |
| 0.0192 | 0.6367 | 800 | 0.0182 | -2.5929 | -3.1225 | 0.6866 | 0.5297 | -462.9526 | -403.5321 | -1.0483 | -1.2122 | 0.0290 | 0.0169 | 0.5789 |
| 0.0233 | 0.7163 | 900 | 0.0237 | -2.3310 | -2.8931 | 0.6810 | 0.5621 | -440.0111 | -377.3470 | -1.3096 | -1.4493 | 0.0387 | 0.0221 | 0.5726 |
| 0.0213 | 0.7959 | 1000 | 0.0219 | -2.4229 | -2.9606 | 0.6931 | 0.5377 | -446.7564 | -386.5316 | -1.4880 | -1.6049 | 0.0357 | 0.0203 | 0.5694 |
| 0.0229 | 0.8754 | 1100 | 0.0231 | -2.2736 | -2.7873 | 0.6950 | 0.5137 | -429.4283 | -371.6010 | -1.5527 | -1.6574 | 0.0379 | 0.0215 | 0.5695 |
| 0.0216 | 0.9550 | 1200 | 0.0227 | -2.3113 | -2.8479 | 0.6931 | 0.5365 | -435.4867 | -375.3782 | -1.4622 | -1.5834 | 0.0374 | 0.0212 | 0.5682 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
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