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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-u4-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-u4-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: 0.0595
- Rewards/chosen: -0.1134
- Rewards/rejected: -0.1090
- Rewards/accuracies: 0.4030
- Rewards/margins: -0.0044
- Logps/rejected: -276.7458
- Logps/chosen: -289.3788
- Logits/rejected: -1.8514
- Logits/chosen: -2.0125
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3803 | 0.4 | 100 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.2725 | 0.8 | 200 | 0.0549 | -0.0209 | -0.0219 | 0.4410 | 0.0010 | -259.3280 | -270.8865 | -1.8361 | -1.9947 |
| 0.3013 | 1.2 | 300 | 0.0532 | -0.1669 | -0.1811 | 0.4675 | 0.0141 | -291.1523 | -300.0851 | -1.8278 | -1.9902 |
| 0.3433 | 1.6 | 400 | 0.0523 | -0.1720 | -0.1893 | 0.4780 | 0.0173 | -292.8069 | -301.0948 | -1.8287 | -1.9909 |
| 0.3606 | 2.0 | 500 | 0.0623 | -0.1514 | -0.1465 | 0.4050 | -0.0048 | -284.2478 | -296.9682 | -1.8491 | -2.0112 |
| 0.3038 | 2.4 | 600 | 0.0616 | -0.1610 | -0.1582 | 0.4090 | -0.0029 | -286.5705 | -298.9020 | -1.8490 | -2.0113 |
| 0.3161 | 2.8 | 700 | 0.0613 | -0.1640 | -0.1619 | 0.4125 | -0.0021 | -287.3163 | -299.4932 | -1.8473 | -2.0096 |
| 0.3852 | 3.2 | 800 | 0.0574 | -0.1342 | -0.1354 | 0.4260 | 0.0012 | -282.0106 | -293.5319 | -1.8537 | -2.0157 |
| 0.3359 | 3.6 | 900 | 0.0595 | -0.1131 | -0.1086 | 0.4005 | -0.0044 | -276.6672 | -289.3095 | -1.8507 | -2.0116 |
| 0.3701 | 4.0 | 1000 | 0.0596 | -0.1134 | -0.1090 | 0.4000 | -0.0044 | -276.7309 | -289.3763 | -1.8513 | -2.0123 |
| 0.4025 | 4.4 | 1100 | 0.0596 | -0.1134 | -0.1088 | 0.4030 | -0.0045 | -276.7074 | -289.3722 | -1.8516 | -2.0127 |
| 0.3754 | 4.8 | 1200 | 0.0595 | -0.1136 | -0.1091 | 0.4010 | -0.0044 | -276.7694 | -289.4114 | -1.8515 | -2.0125 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |