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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-gen-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-gen-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: 0.0550
- Rewards/chosen: -0.0251
- Rewards/rejected: -0.0231
- Rewards/accuracies: 0.3875
- Rewards/margins: -0.0020
- Logps/rejected: -278.0226
- Logps/chosen: -291.8019
- Logits/rejected: -1.7909
- Logits/chosen: -1.9487
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3754 | 0.08 | 100 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.3556 | 0.16 | 200 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.3556 | 0.24 | 300 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.3606 | 0.32 | 400 | 0.0537 | 0.0 | 0.0 | 0.0 | 0.0 | -254.9398 | -266.6976 | -1.8067 | -1.9618 |
| 0.3606 | 0.4 | 500 | 0.0586 | -0.0343 | -0.0263 | 0.3125 | -0.0079 | -281.2869 | -300.9843 | -1.7627 | -1.9202 |
| 0.3408 | 0.48 | 600 | 0.0587 | -0.0387 | -0.0304 | 0.3120 | -0.0083 | -285.3777 | -305.4413 | -1.7361 | -1.8917 |
| 0.3359 | 0.56 | 700 | 0.0587 | -0.0387 | -0.0304 | 0.3095 | -0.0083 | -285.3294 | -305.3720 | -1.7363 | -1.8920 |
| 0.3507 | 0.64 | 800 | 0.0569 | -0.0251 | -0.0199 | 0.3215 | -0.0052 | -274.8357 | -291.8357 | -1.8172 | -1.9784 |
| 0.3926 | 0.72 | 900 | 0.0550 | -0.0245 | -0.0224 | 0.3840 | -0.0021 | -277.3842 | -291.2067 | -1.7982 | -1.9565 |
| 0.3655 | 0.8 | 1000 | 0.0549 | -0.0254 | -0.0235 | 0.3860 | -0.0019 | -278.4594 | -292.0937 | -1.7905 | -1.9482 |
| 0.3682 | 0.88 | 1100 | 0.0549 | -0.0253 | -0.0234 | 0.3850 | -0.0020 | -278.3317 | -292.0442 | -1.7919 | -1.9497 |
| 0.3531 | 0.96 | 1200 | 0.0550 | -0.0251 | -0.0231 | 0.3910 | -0.0020 | -278.0787 | -291.8378 | -1.7915 | -1.9493 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |