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---
base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1
datasets:
- argilla/dpo-mix-7k
- RedaAlami/PKU-SafeRLHF-Processed
library_name: peft
license: other
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-gemma-dpo
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. -->
# zephyr-7b-gemma-dpo
This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-gemma-sft-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-sft-v0.1) on the argilla/dpo-mix-7k and the RedaAlami/PKU-SafeRLHF-Processed datasets.
It achieves the following results on the evaluation set:
- Loss: 0.6478
- Rewards/chosen: -0.3452
- Rewards/rejected: -0.5788
- Rewards/accuracies: 0.6169
- Rewards/margins: 0.2336
- Logps/rejected: -334.5554
- Logps/chosen: -295.9647
- Logits/rejected: 436.0139
- Logits/chosen: 452.6414
## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7052 | 0.2602 | 100 | 0.7032 | 0.1828 | 0.1374 | 0.5148 | 0.0454 | -320.2303 | -285.4035 | 437.8931 | 454.4476 |
| 0.6851 | 0.5205 | 200 | 0.6794 | 0.1534 | 0.0240 | 0.5991 | 0.1294 | -322.4987 | -285.9917 | 436.5674 | 453.2177 |
| 0.6545 | 0.7807 | 300 | 0.6632 | -0.0335 | -0.2290 | 0.5962 | 0.1955 | -327.5587 | -289.7299 | 435.9517 | 452.6035 |
| 0.6428 | 1.0410 | 400 | 0.6532 | -0.3583 | -0.5844 | 0.6154 | 0.2261 | -334.6671 | -296.2265 | 436.0371 | 452.6768 |
| 0.6366 | 1.3012 | 500 | 0.6521 | -0.3063 | -0.5602 | 0.6124 | 0.2539 | -334.1831 | -295.1856 | 436.1843 | 452.8112 |
| 0.6058 | 1.5615 | 600 | 0.6497 | -0.3389 | -0.5751 | 0.6139 | 0.2362 | -334.4804 | -295.8380 | 436.0276 | 452.6521 |
| 0.6368 | 1.8217 | 700 | 0.6449 | -0.3403 | -0.5854 | 0.6065 | 0.2451 | -334.6864 | -295.8665 | 436.0117 | 452.6395 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |