zephyr-7b-gpo-iter1 / README.md
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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: zephyr-7b-gpo-iter1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-gpo-iter1
This model is a fine-tuned version of [DUAL-GPO/zephyr-7b-gpo-iter0](https://huggingface.co/DUAL-GPO/zephyr-7b-gpo-iter0) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0069
- Rewards/chosen: 0.0025
- Rewards/rejected: 0.0081
- Rewards/accuracies: 0.4595
- Rewards/margins: -0.0056
- Logps/rejected: -272.5866
- Logps/chosen: -298.8498
- Logits/rejected: -2.1749
- Logits/chosen: -2.3692
## 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: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0006 | 0.2 | 100 | 0.0031 | -0.0541 | -0.0467 | 0.4245 | -0.0074 | -278.0669 | -304.5065 | -2.1506 | -2.3436 |
| 0.0025 | 0.4 | 200 | 0.0033 | -0.0115 | -0.0107 | 0.4910 | -0.0008 | -274.4619 | -300.2420 | -2.1684 | -2.3612 |
| 0.0009 | 0.6 | 300 | 0.0030 | -0.0220 | -0.0216 | 0.4935 | -0.0004 | -275.5567 | -301.2960 | -2.1427 | -2.3360 |
| 0.0013 | 0.8 | 400 | 0.0034 | -0.0156 | -0.0142 | 0.4935 | -0.0014 | -274.8156 | -300.6561 | -2.1462 | -2.3405 |
| 0.0011 | 1.0 | 500 | 0.0037 | -0.0565 | -0.0502 | 0.4520 | -0.0063 | -278.4165 | -304.7457 | -2.1454 | -2.3392 |
| 0.0116 | 1.2 | 600 | 0.0049 | -0.0283 | -0.0229 | 0.4435 | -0.0054 | -275.6791 | -301.9266 | -2.1527 | -2.3449 |
| 0.015 | 1.4 | 700 | 0.0065 | -0.0261 | -0.0182 | 0.4450 | -0.0078 | -275.2170 | -301.7041 | -2.1650 | -2.3586 |
| 0.0009 | 1.6 | 800 | 0.0069 | 0.0079 | 0.0124 | 0.4720 | -0.0044 | -272.1540 | -298.3011 | -2.1746 | -2.3689 |
| 0.0109 | 1.8 | 900 | 0.0069 | 0.0024 | 0.0080 | 0.4570 | -0.0057 | -272.5880 | -298.8583 | -2.1739 | -2.3682 |
| 0.0015 | 2.0 | 1000 | 0.0069 | 0.0025 | 0.0081 | 0.4595 | -0.0056 | -272.5866 | -298.8498 | -2.1749 | -2.3692 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2