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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-u3-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-u3-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: 0.0976
- Rewards/chosen: -0.2046
- Rewards/rejected: -0.1684
- Rewards/accuracies: 0.3440
- Rewards/margins: -0.0362
- Logps/rejected: -271.7846
- Logps/chosen: -287.1580
- Logits/rejected: -1.8253
- Logits/chosen: -1.9851
## 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 |
| 0.2732 | 0.8 | 200 | 0.0585 | -0.0406 | -0.0433 | 0.4405 | 0.0028 | -259.2744 | -270.7553 | -1.8367 | -1.9952 |
| 0.3013 | 1.2 | 300 | 0.0800 | -0.3312 | -0.3632 | 0.4645 | 0.0319 | -291.2575 | -299.8226 | -1.8131 | -1.9752 |
| 0.3433 | 1.6 | 400 | 0.0812 | -0.3364 | -0.3695 | 0.4675 | 0.0331 | -291.8892 | -300.3361 | -1.8102 | -1.9721 |
| 0.3606 | 2.0 | 500 | 0.1100 | -0.3181 | -0.2920 | 0.3735 | -0.0262 | -284.1371 | -298.5123 | -1.8348 | -1.9970 |
| 0.3038 | 2.4 | 600 | 0.1092 | -0.3233 | -0.2979 | 0.3770 | -0.0254 | -284.7261 | -299.0256 | -1.8317 | -1.9936 |
| 0.3161 | 2.8 | 700 | 0.1069 | -0.3172 | -0.2929 | 0.3800 | -0.0243 | -284.2322 | -298.4158 | -1.8345 | -1.9966 |
| 0.3852 | 3.2 | 800 | 0.0918 | -0.2304 | -0.2057 | 0.3685 | -0.0247 | -275.5103 | -289.7388 | -1.8409 | -2.0019 |
| 0.3359 | 3.6 | 900 | 0.0983 | -0.2063 | -0.1696 | 0.3430 | -0.0368 | -271.8958 | -287.3323 | -1.8240 | -1.9838 |
| 0.3701 | 4.0 | 1000 | 0.0982 | -0.2062 | -0.1693 | 0.3455 | -0.0368 | -271.8734 | -287.3159 | -1.8241 | -1.9838 |
| 0.4025 | 4.4 | 1100 | 0.0975 | -0.2047 | -0.1687 | 0.3455 | -0.0359 | -271.8127 | -287.1649 | -1.8260 | -1.9858 |
| 0.3754 | 4.8 | 1200 | 0.0974 | -0.2044 | -0.1685 | 0.3440 | -0.0359 | -271.7890 | -287.1331 | -1.8256 | -1.9853 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |