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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-gpo-update3-i1
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-gpo-update3-i1
This model is a fine-tuned version of [DUAL-GPO/zephyr-7b-gpo-update3-i0](https://huggingface.co/DUAL-GPO/zephyr-7b-gpo-update3-i0) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0574
- Rewards/chosen: -0.0003
- Rewards/rejected: 0.0038
- Rewards/accuracies: 0.3765
- Rewards/margins: -0.0041
- Logps/rejected: -254.1840
- Logps/chosen: -266.7596
- Logits/rejected: -1.8151
- Logits/chosen: -1.9709
## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0013 | 0.4 | 100 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.0013 | 0.8 | 200 | 0.0575 | -0.0013 | 0.0029 | 0.3800 | -0.0041 | -254.3691 | -266.9557 | -1.8139 | -1.9695 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |